Shape measurement method, shape measurement device, and program

Abstract

Embodiments of the present application relate to a shape measurement method, a shape measurement apparatus, and a program. In the shape measurement method of the embodiments, a converged value of a parameter included in a first parameter group is calculated by a first fitting process using a scattering intensity curve and a first assumed scattering intensity curve, the scattering intensity curve relating to a scattering intensity of an electromagnetic wave irradiated on a substrate having a specific pattern, the first assumed scattering intensity curve relating to a scattering intensity calculated by performing a first simulation on a first virtual configuration, the first virtual configuration being configured based on the first parameter group composed of a plurality of parameters including a focus parameter. A converged value of a parameter included in a second parameter group is calculated by a second fitting process using the scattering intensity curve and a second assumed scattering intensity curve, the second assumed scattering intensity curve relating to a scattering intensity calculated by performing a second simulation on a second virtual configuration, the second virtual configuration being configured based on the second parameter group composed of a plurality of parameters including the focus parameter and the converged value of the focus parameter being set as a constant.

Description

[0001] [CROSS-REFERENCE TO RELATED APPLICATIONS]

[0002] This application is based on and claims priority pursuant to Japanese Patent Application No. 2021-115748, filed on July 13, 2021, the entire content of which is incorporated herein by reference. TECHNICAL FIELD

[0003] An embodiment of the present application relates to a shape measurement method, a shape measurement apparatus, and a program. BACKGROUND

[0004] In a semiconductor manufacturing process, a micro-angle incidence X-ray small-angle scattering method (Grazing Incidence Small Angle X-ray Scattering; hereinafter referred to as GISAXS) is used as a technique for measuring the shape of a pattern formed on a substrate. In GISAXS, a technique is used in which a virtual structure is assumed based on a plurality of parameters that represent the shape characteristics of a pattern, a convergence value of each parameter is calculated by performing a simulation or a fitting process on the virtual structure, and thus the shape of the pattern is measured. Among the plurality of parameters that constitute the virtual structure, there are parameters that are difficult to accurately calculate the convergence value. A decrease in the accuracy of the convergence value of the parameters can lead to a decrease in the measurement accuracy of the pattern shape. SUMMARY

[0005] An embodiment of the present application provides a shape measurement method, a shape measurement apparatus, and a program that can measure the shape of a pattern with high accuracy.

[0006] According to an embodiment of the present application, a shape measurement method is provided. In the shape measurement method, a scattering intensity curve is obtained, the scattering intensity curve being related to the scattering intensity of an electromagnetic wave that is irradiated from a first device to a substrate having a specific pattern. Further, a first assumed scattering intensity curve is obtained, the first assumed scattering intensity curve being related to the scattering intensity that is calculated by performing a first simulation on a first virtual structure, the first virtual structure being constituted based on a first parameter group composed of a plurality of parameters including a focus parameter. Further, a convergence value of a parameter included in the first parameter group is calculated by a first fitting process using the scattering intensity curve and the first assumed scattering intensity curve. Further, a second assumed scattering intensity curve is obtained, the second assumed scattering intensity curve being related to the scattering intensity that is calculated by performing a second simulation on a second virtual structure, the second virtual structure being constituted based on a second parameter group composed of a plurality of parameters including the focus parameter and the convergence value of the focus parameter being set to a constant. Further, a convergence value of a parameter included in the second parameter group is calculated by a second fitting process using the scattering intensity curve and the second assumed scattering intensity curve.

[0007] Based on the aforementioned configuration, a shape measurement method, shape measurement device, and program capable of measuring pattern shapes with high precision can be provided. Attached Figure Description

[0008] Figure 1 This is a diagram showing an example of the configuration of the shape measuring device according to the first embodiment.

[0009] Figure 2 This is a top view showing an example of the pattern of the substrate in the first embodiment.

[0010] Figure 3 This is a block diagram illustrating an example of the hardware configuration of the control unit and the arithmetic unit in the first embodiment.

[0011] Figure 4 This is a block diagram illustrating an example of the functional configuration of the arithmetic unit in the first embodiment.

[0012] Figure 5 This is a graph showing an example of the scattering intensity curve of the first embodiment.

[0013] Figure 6 This is a diagram illustrating an example of the first virtual structure of the first embodiment.

[0014] Figure 7 This is a diagram illustrating an example of the second virtual structure of the first embodiment.

[0015] Figure 8 This is a flowchart illustrating an example of the processing involved in generating shape information in the shape measuring apparatus of the first embodiment.

[0016] Figure 9 This is a block diagram illustrating an example of the functional configuration of the arithmetic unit in the second embodiment.

[0017] Figure 10 This is a graph illustrating an example of the relationship between the baseline value and the convergence value of the key parameter before correction in the second embodiment.

[0018] Figure 11 This is a graph illustrating an example of the relationship between the baseline value and the convergence value of the modified key parameter in the second embodiment.

[0019] Figure 12 This is a flowchart illustrating an example of the process for correcting the convergence value of key parameters in the second embodiment. Detailed Implementation

[0020] Hereinafter, the shape measurement method and shape measurement apparatus of the embodiments will be described in detail with reference to the accompanying drawings. However, the present invention is not limited to these embodiments.

[0021] (First Embodiment)Figure 1 This diagram illustrates an example of the configuration of the shape measuring device 1 according to the first embodiment. Hereinafter, the case where the shape measuring device 1 is a GISAXS will be illustrated.

[0022] The shape measuring device 1 includes: a stage 11, an X-ray tube 12 (an example of the first device), a diverging slit 13, a two-dimensional detector 14, a control unit 20, and a computing unit 30.

[0023] The stage 11 is a unit for placing the substrate 40 to be measured. The stage 11 can be moved in a direction parallel to the mounting surface of the substrate 10 by a suitable drive mechanism, and can be rotated in a plane parallel to the mounting surface.

[0024] A specific pattern is formed on the substrate 40. The pattern includes a structure formed by the periodic repetition of unit structures consisting of recesses or convexities, such as line and gap patterns, through-hole patterns (memory holes), pillar patterns, etc. of semiconductor memory devices.

[0025] Figure 2 This is a top view showing an example of the pattern P of the substrate 40 according to the first embodiment. In the figure, the XY plane is a plane parallel to the mounting surface of the stage 11, and the Z-axis is a direction perpendicular to the XY plane. The pattern P illustrated here is a line and gap pattern, including a first gap portion 41, a second gap portion 42, and a line portion 45. The first gap portion 41 and the second gap portion 42 are recesses formed along the Y-axis from the surface of the substrate 40 toward the interior of the substrate 40 (the negative direction of the Z-axis). The width of the second gap portion 42 in the X direction is greater than the width of the first gap portion 41 in the X direction. The line portion 45 is a protrusion formed between the first gap portion 41 and the second gap portion 42. The unit structure C is composed of one first gap portion 41, one second gap portion 42, and two line portions 45. In top view, the unit structure C is arranged in a two-dimensional and periodic manner. In this embodiment, Figure 2 In this context, a unit structure C is defined as the portion extending from the middle of the line portion 45 adjacent to the left side of the first gap portion 41 in the X-axis direction to the middle of the line portion 45 adjacent to the right side of the second gap portion 42 in the X-axis direction. However, the method of dividing the unit structure C is not limited to this. Furthermore, Figure 2 The pattern P shown is an example, and the pattern formed on the substrate 40 is not limited to line and gap patterns.

[0026] The X-ray tube 12 is a unit that includes a light source that generates X-rays (an example of electromagnetic waves) of a specific wavelength, and a concave mirror. The light source is not particularly limited as long as it generates X-rays; for example, it could be a light source that generates Kα rays from Cu. The X-ray tube 12 generates incident X-rays Li with a wavelength of, for example, less than 1 nm, based on a control signal from the control unit 20. The incident X-rays Li are irradiated onto the substrate 40 at a desired incident angle α by adjusting the optical path through the concave mirror within the X-ray tube 12. The incident X-rays Li are scattered by the pattern P on the substrate 40, thus generating scattered X-rays Lo. The scattered X-rays Lo are scattered from the substrate 40 at various exit angles β depending on the shape of the pattern P.

[0027] The diverging slit 13 is a slit used to adjust the width of the incident X-ray Li. When it is desired to increase the intensity of the incident X-ray Li, the width of the diverging slit 13 is widened according to the control signal from the control unit 20.

[0028] A two-dimensional detector 14 is positioned sufficiently far from the substrate 40 (pattern P) to detect scattered X-rays Lo using light-receiving elements and measure the intensity (scattering intensity) of the scattered X-rays Lo. The two-dimensional detector 14 has a light-receiving section with light-receiving elements arranged in a two-dimensional configuration. Each light-receiving element measures the intensity of the scattered X-rays Lo. By establishing a correspondence between the scattering intensity measured by each light-receiving element and the position of each light-receiving element, a two-dimensional image representing the scattering intensity distribution can be generated. The two-dimensional detector 14 outputs detection data (e.g., data representing the two-dimensional image) representing the detection result of the scattering intensity to the processing unit 30.

[0029] The control unit 20 is an information processing device that performs processing to control the stage 11, X-ray tube 12, diverging slit 13, etc. The control unit 20 adjusts the position of the incident X-rays Li on the substrate 40 by displacing the stage 11. Furthermore, the control unit 20 controls the incident angle α of the incident X-rays Li incident on the substrate 40, the output of the incident X-rays Li, etc. Additionally, the control unit 20 controls the width of the diverging slit 13 to adjust the irradiation area of ​​the incident X-rays Li. Furthermore, the control unit 20 sets the measurement conditions for measuring the substrate 40 for the stage control unit 21, the light source control unit 22, the slit width control unit 23, and the calculation unit 30. The measurement conditions include, for example, the incident angle α, the slit width, and the rotational speed of the stage 11.

[0030] The arithmetic unit 30 is an information processing device that performs processing based on the detection data output from the two-dimensional detector 14 to measure the shape of the pattern P formed on the substrate 40. The function of the arithmetic unit 30 will be described below.

[0031] Figure 3This is a block diagram illustrating an example of the hardware configuration of the control unit 20 and the arithmetic unit 30 in the first embodiment. The control unit 20 and arithmetic unit 30 illustrated here include a microcomputer (processor) connected via a bus 57, such as a CPU (Central Processing Unit) 51, a ROM (Read Only Memory) 52, a RAM (Random Access Memory) 53, an external storage device 54, an output device 55, and an input device 56. The CPU 51 performs various arithmetic operations according to programs stored in the ROM 52, external storage device 54, etc. The RAM 53 serves as the working area of ​​the CPU 51. The output device 55 can be, for example, a display or a speaker. The input device 56 can be, for example, a keyboard, a touch panel mechanism, or a pointing device. Furthermore, the hardware configuration of the control unit 20 and the arithmetic unit 30 is not limited to the above description and can also be constructed using devices such as ASICs (Application Specific Integrated Circuits) or FPGAs (Field Programmable Gate Arrays).

[0032] Figure 4 This is a block diagram illustrating an example of the functional configuration of the arithmetic unit 30 in the first embodiment. The arithmetic unit 30 includes: a scattering intensity curve acquisition unit 101, a first simulation unit 102, a first fitting unit 103, a second simulation unit 104, a second fitting unit 105, and a shape information generation unit 106. These functional components 101 to 106 can be generated by, for example, through... Figure 3 It is achieved through the collaboration of the hardware and software (program) shown.

[0033] The scattering intensity curve acquisition unit 101 acquires a scattering intensity curve, which is related to the scattering intensity of electromagnetic waves irradiating the substrate 40. In this embodiment, the scattering intensity curve acquisition unit 101 acquires (generates) a scattering intensity curve related to the scattering intensity when incident X-rays Li are actually irradiated onto the substrate 40, based on detection data output from the two-dimensional detector 14.

[0034] Figure 5 This is a graph illustrating an example of the scattering intensity curve of the first embodiment. The scattering intensity curve illustrated here shows the relationship between the emission angle β (horizontal axis) of the scattered X-ray Lo and the intensity (vertical axis) of the scattered X-ray Lo.

[0035] First Simulation Unit 102 ( Figure 4A first hypothetical scattering curve is obtained by performing a first simulation on a first virtual structure based on the first parameter group. The first parameter group is a group of multiple parameters representing the shape characteristics of the pattern P, which is the object of measurement, and includes key parameters. Key parameters are parameters pre-selected from the multiple parameters, such as parameters whose convergence values ​​are relatively difficult to calculate through the final fitting process (the second fitting process described below). The first virtual structure is a virtual structure constructed based on the first parameter group as described above.

[0036] Figure 6 This diagram illustrates an example of the first virtual structure M1 in the first embodiment. The first virtual structure M1 illustrated here simply represents... Figure 2 The shape characteristics of the unit structure C of the pattern P illustrated herein, wherein the first virtual structure M1 is defined by the height H, the first width S1, the second width S2, the line width CD, and the width difference ds.

[0037] Height H represents the height (depth) from the bottom to the top of the first gap 41 and the second gap 42. First width S1 represents the width of the first gap 41 in the X-axis direction, assuming a fixed width across the entire height. Second width S2 represents the width of the second gap 42 in the X-axis direction, assuming a fixed width across the entire height. Line width CD represents the distance between the first gap 41 and the second gap 42, assuming fixed widths across the entire height for both the first gap 41 and the second gap 42. Width difference ds represents the difference (S2 - S1) between the first width S1 and the second width S2. In this embodiment, the width difference ds is set as a critical parameter.

[0038] First Simulation Unit 102 ( Figure 4 A first simulation is performed on the first virtual structure M1 as described above. The first simulation is a process of inferring the scattering intensity when incident X-rays L are irradiated onto the first virtual structure M1 under specific measurement conditions. Through this first simulation, a first inferring scattering curve is obtained (generated), which is related to the scattering intensity when incident X-rays Li are irradiated onto the first virtual structure M1. The first inferring scattering curve and... Figure 5 Similarly, the illustrated scattering intensity curve shows the relationship between the emission angle β of the scattered X-ray Lo and the intensity of the scattered X-ray Lo.

[0039] The first fitting unit 103 calculates the convergence value of the parameters included in the first parameter group by performing a first fitting process using the scattering intensity curve and the first inferred scattering intensity curve. In the first fitting process, the scattering intensity of the scattering intensity curve is compared with the scattering intensity of the first inferred scattering intensity curve obtained by changing the value of the parameter. When the difference between the two scattering intensities is below a threshold, the value of the parameter included in the first parameter group at this time is set as the convergence value.

[0040] The second simulation unit 104 performs a second simulation on a second virtual structure based on the second parameter group to obtain a second hypothetical scattering curve. The second parameter group consists of multiple parameters, including key parameters, and the convergence value calculated by the first fitting unit 103 (the convergence value calculated using the first virtual structure M1) among the key parameters is set to a constant. The second virtual structure is a virtual structure constructed based on this second parameter group.

[0041] Figure 7 This diagram illustrates an example of the second virtual structure M2 in the first embodiment. The second virtual structure M2 illustrated here is shown in more detail than the first virtual structure M1. Figure 2 The shape characteristics of the unit structure C of the pattern P illustrated herein. The second virtual structure M2 is defined by the following parameters: height H, first width S1, second width S2, line width CD, first bottom radius of curvature RB1, second bottom radius of curvature RB2, first upper radius of curvature RT1, second upper radius of curvature RT2, first gap tilt angle SWA1, second gap tilt angle SWA2, and width difference ds. Among the width difference ds, which is the key parameter, the convergence value calculated by the first fitting unit 103 is set as a constant K.

[0042] Height H represents the height (depth) from the bottom (center of the bottom) to the top of the first gap 41 and the second gap 42. First width S1 represents the width of the first gap 41 in the X-axis direction at the H / 2 position. Second width S2 represents the width of the second gap 42 in the X-axis direction at the H / 2 position. Line width CD represents the distance between the first gap 41 and the second gap 42 at the H / 2 position. First bottom radius of curvature RB1 represents the radius of curvature of the bottom of the first gap 41. Second bottom radius of curvature RB2 represents the radius of curvature of the bottom of the second gap 42. First upper radius of curvature RT1 represents the radius of curvature of the portion of the line portion 45 on the side of the first gap 41. Second upper radius of curvature RT2 represents the radius of curvature of the portion of the line portion 45 on the side of the second gap 42. First gap tilt angle SWA1 represents the tilt angle of the side of the first gap 41 relative to the horizontal plane (XY plane). The tilt angle SWA2 of the second gap represents the tilt angle of the side of the second gap 42 relative to the horizontal plane. The width difference ds represents the difference (S2-S1) between the first width S1 and the second width S2, which is fixed as a constant K (the convergence value calculated through the first fitting process).

[0043] 2nd Simulation Section 104 ( Figure 4 A second simulation is performed on the second virtual structure M2 as described above. The second simulation is a process of inferring the scattering intensity when incident X-rays Li are irradiated onto the second virtual structure M2 under specific measurement conditions. Through this second simulation, a second inferring scattering curve is obtained (generated), which is related to the scattering intensity when incident X-rays Li are irradiated onto the second virtual structure M2. The second inferring scattering curve is related to... Figure 5 Similarly, the scattering intensity curve illustrated in the figure shows the relationship between the emission angle β of the scattered X-ray Lo and the intensity of the scattered X-ray Lo.

[0044] The second fitting unit 105 calculates the convergence value of each parameter included in the second parameter group by performing a second fitting process using the scattering intensity curve and the second inferred scattering intensity curve. In this embodiment, the parameters included in the second parameter group are height H, first width S1, second width S2, line width CD, first bottom curvature radius RB1, second bottom curvature radius RB2, first upper curvature radius RT1, second upper curvature radius RT2, first gap tilt angle SWA1, second gap tilt angle SWA2, and width difference ds (constant K). In the second fitting process, the scattering intensity of the scattering intensity curve is compared with the scattering intensity of the second inferred scattering intensity curve obtained by changing the parameters. When the difference between the two scattering intensities is below a threshold, the value of each parameter at this time is set as the convergence value.

[0045] The shape information generation unit 106 generates shape information related to the shape of the measured object pattern P based on the convergence value of each parameter included in the second parameter group. The shape information can be used in various ways, such as for quality evaluation of the substrate 40 and control of the apparatus for forming the pattern P on the substrate 40.

[0046] Figure 8 This is a flowchart illustrating an example of the processing involved in generating shape information in the shape measuring device 1 of the first embodiment. The scattering intensity curve acquisition unit 101 acquires a scattering intensity curve based on detection data from the two-dimensional detector 14 (S101). The first simulation unit 102 sets a first virtual structure M1 based on a first group of parameters including a key parameter (e.g., width difference ds) (S102), performs a first simulation on the first virtual structure M1, and acquires a first virtual scattering intensity curve (S103).

[0047] The first fitting unit 103 calculates the convergence value of the parameters included in the first parameter group by performing a first fitting process using the scattering intensity curve and the first virtual scattering intensity curve (S104). The second simulation unit 104 sets a second virtual structure M2 based on a second parameter group with the key parameter fixed as the convergence value (constant K) (S105), performs a second simulation on the second virtual structure M2, and obtains the second virtual scattering intensity curve (S106).

[0048] The second fitting unit 105 calculates the convergence value of each parameter included in the second parameter group by performing a second fitting process using the scattering intensity curve and the second virtual scattering intensity curve (S107). The shape information generation unit 106 generates shape information related to the shape of the pattern P based on the convergence value of the second parameter group (S108).

[0049] Based on the aforementioned configuration, calculations are performed using a virtual construct (first virtual construct M1) with relatively simple convergence values ​​for the key parameters. This reduces the processing load when using a complex virtual construct (second virtual construct M2) for processing (second simulation and second fitting processing), or prevents the key parameters from converging to erroneous values. Consequently, the shape of the pattern can be measured with high accuracy.

[0050] Hereinafter, other embodiments will be described with reference to the accompanying drawings. The same or identical parts as in the first embodiment will be marked with the same symbols, and their descriptions will sometimes be omitted.

[0051] (Second Implementation) Figure 9 This is a block diagram illustrating an example of the functional configuration of the arithmetic unit 30 in the second embodiment. The arithmetic unit 30 of this embodiment differs from that of the first embodiment in that it includes a reference value acquisition unit 201 and a correction unit 202 as components for correcting the convergence value of the key parameters.

[0052] The reference value acquisition unit 201 acquires a reference value, which is used in conjunction with the irradiation to acquire the scattering intensity curve. Figure 5 The value of the key parameter is measured by a device (second device) different from the device (X-ray tube 12: first device) that irradiates the substrate 40 with electromagnetic waves (incident X-rays Li). The second device may, for example, be a device that measures the value of the key parameter by irradiating the substrate 40 with electromagnetic waves having a wavelength different from the incident X-rays Li. In this case, the second device may be, for example, a CD-SEM (Critical Dimension Scanning Electron Microscope). Furthermore, the second device may also be a device that measures the value of the key parameter by destructively inspecting a sample substrate with a pattern P that is different from the actual substrate 40 (placed on the stage 11) being measured. In this case, the second device may be, for example, an X-SEM (X-Ray scanning electron microscopy), an X-TEM (X-Ray Transmission Electron Microscope), etc.

[0053] The correction unit 202 corrects the convergence value of the key parameter calculated by the first fitting unit 103 based on the reference value (the value of the key parameter measured by the second device) obtained by the reference value acquisition unit 201. The correction unit 202 sets a correction coefficient to correct the convergence value based on the difference between the convergence value of the key parameter calculated by the first fitting process (first fitting unit 103) and the reference value obtained by the reference value acquisition unit 201.

[0054] Figure 10 This is a graph illustrating an example of the relationship between the baseline value and the convergence value of the key parameter before correction in the second embodiment. In this graph, the horizontal axis corresponds to the baseline value, and the vertical axis corresponds to the convergence value of the key parameter before correction. In this example, the value measured by X-TEM is used as the baseline value. Line L represents the correspondence between the baseline value and the convergence value; if there is no error between the two, the slope is 1, and the offset (the value of the convergence value when the baseline value is 0) is 0, but... Figure 10 In the example shown, the slope is 0.599 and the offset is 0.386. The correction unit 202 sets a correction coefficient such that the error of this slope and offset is below a threshold.

[0055] Figure 11This is a graph illustrating an example of the relationship between the baseline value and the convergence value of the corrected key parameter in the second embodiment. In this graph, the horizontal axis corresponds to the baseline value, and the vertical axis corresponds to the convergence value of the corrected key parameter. For example... Figure 11 As shown, in the corrected line L, the slope is close to 1 and the offset is close to 0.

[0056] Figure 12 This is a flowchart illustrating an example of the process for correcting the convergence value of the key parameter in the second embodiment. The reference value acquisition unit 201 measures the value of the key parameter in the substrate 40 or sample substrate, which is actually being measured, using the second device, and acquires the measured value as a reference value (S201). The correction unit 202 sets a correction coefficient to correct the convergence value based on the difference between the convergence value of the key parameter calculated through the first fitting process (first fitting unit 103) and the reference value acquired by the reference value acquisition unit 201 (S202). The correction unit 202 corrects the convergence value based on the correction coefficient (S203) and outputs the corrected convergence value as a constant K for the key parameter to the second simulation unit 104 (S204).

[0057] According to this embodiment, the calculation accuracy of the convergence value of key parameters can be improved, and the measurement accuracy of the shape of pattern P can be improved.

[0058] Programs that enable a computer to perform the various processes or functions described in the embodiments are provided as installable or executable files stored on computer-readable recording media such as CD-ROM (Compact Disc Read-Only Memory), floppy disk (FD), CD-R (CD Recordable), and DVD (Digital Versatile Disk). Alternatively, the program may be configured to be stored on a computer connected to a network such as the Internet, and provided by downloading the program via the network. Furthermore, the program may be provided or distributed via a network such as the Internet. Additionally, the program may be provided by pre-assembling it in ROM or the like.

[0059] Several embodiments of the present invention have been described, but these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other ways, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments or variations thereof are included in the scope or spirit of the invention, and are included within the scope of the invention as set forth in the claims and their equivalents.

Claims

1. A shape measurement method comprising the steps of: acquiring a scattering intensity curve relating to the scattering intensity of electromagnetic waves irradiated from a first device onto a substrate having a specific pattern; acquiring a first hypothetical scattering intensity curve relating to a scattering intensity calculated by performing a first simulation on a first virtual structure, the first virtual structure being constructed based on a first parameter group consisting of multiple parameters including key parameters; calculating convergence values ​​of parameters included in the first parameter group by performing a first fitting process using the scattering intensity curve and the first hypothetical scattering intensity curve; acquiring a second hypothetical scattering intensity curve relating to a scattering intensity calculated by performing a second simulation on a second virtual structure, the second virtual structure being constructed based on a second parameter group consisting of multiple parameters including the key parameters, wherein the convergence value in the key parameters is set to a constant; and calculating convergence values ​​of parameters included in the second parameter group by performing a second fitting process using the scattering intensity curve and the second hypothetical scattering intensity curve.

2. The shape measurement method according to claim 1, further comprising the step of: correcting the convergence value of the key parameter calculated by the first fitting process based on the value of the key parameter, i.e., the reference value, measured by a second device different from the first device.

3. The shape measurement method according to claim 2, wherein the second device uses electromagnetic waves to measure the reference value, the electromagnetic waves having a different wavelength than the electromagnetic waves irradiated from the first device.

4. The shape measurement method according to claim 2, wherein the second device is a CD-SEM.

5. The shape measurement method according to claim 2, wherein the second device measures the reference value by performing a destructive inspection on a sample substrate having the pattern and different from the substrate.

6. The shape measurement method according to claim 5, wherein the second device is an X-SEM or an X-TEM.

7. A shape measuring device, comprising: a scattering intensity curve acquisition unit for acquiring a scattering intensity curve related to the scattering intensity of electromagnetic waves irradiated from a first device onto a substrate having a specific pattern; a first simulation unit for acquiring a first hypothetical scattering intensity curve related to a scattering intensity calculated by performing a first simulation on a first virtual structure, the first virtual structure being constructed based on a first parameter group consisting of multiple parameters including key parameters; and a first fitting unit for performing a first fitting using the scattering intensity curve and the first hypothetical scattering intensity curve. The system comprises: a first parameter group and a second simulation unit, which calculates the convergence value of the parameters contained in the first parameter group; a second simulation unit, which acquires a second hypothetical scattering intensity curve, which is related to the scattering intensity calculated by performing a second simulation on a second virtual structure, the second virtual structure being constructed based on a second parameter group consisting of multiple parameters including the key parameter, and the convergence value of the key parameter being set to a constant; and a second fitting unit, which calculates the convergence value of the parameters contained in the second parameter group by performing a second fitting process using the scattering intensity curve and the second hypothetical scattering intensity curve.

8. A recording medium storing a program that causes a computer to perform the following processing: acquiring a scattering intensity curve relating to the scattering intensity of electromagnetic waves irradiated from a first device onto a substrate having a specific pattern; acquiring a first hypothetical scattering intensity curve relating to a scattering intensity calculated by performing a first simulation on a first virtual structure, the first virtual structure being based on a first parameter group consisting of a plurality of parameters including a key parameter; calculating convergence values ​​of the parameters included in the first parameter group by performing a first fitting process using the scattering intensity curve and the first hypothetical scattering intensity curve; acquiring a second hypothetical scattering intensity curve relating to a scattering intensity calculated by performing a second simulation on a second virtual structure, the second virtual structure being based on a second parameter group consisting of a plurality of parameters including the key parameter, wherein the convergence value in the key parameter is set to a constant; and calculating convergence values ​​of the parameters included in the second parameter group by performing a second fitting process using the scattering intensity curve and the second hypothetical scattering intensity curve.

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