Optical filtering device, computational spectrometer, and spectrum reconstruction method

Abstract

The present invention discloses an optical filtering device, a computational spectrometer, and a spectrum reconstruction method. The optical filtering device comprises a multi-microring resonator parallel structure formed by cascading a plurality of uplink and downlink microring resonators, each of which is provided with an adjustable phase shifter. The input port separates TE light and TM light via a polarization beam splitter and is respectively connected to one end of an upper waveguide and a lower waveguide of the multi-microring resonator parallel structure. The other ends of the upper and lower waveguides each output TE light and TM light independently via the polarization beam splitter. The scheme uses an inverse design algorithm to adjust the structural parameters of the optical filtering device so that its spectral transmission line has greater randomness, thereby achieving an ideal autocorrelation width. The adjustable phase shifter realizes variable filtering behavior, and the spectra of TE light and TM light can be reconstructed separately.

Description

Technical Field

[0001] The present invention relates to the technical field of computational spectroscopy analysis instruments, and in particular to an optical filtering device, a computational spectrometer, and a spectrum reconstruction method. Background Art

[0002] Light is the carrier of information transmission. As a key instrument for detecting spectra, spectrometers are widely used in fields such as electronic communications, agricultural production, food manufacturing, aerospace, and geoscience. Traditional spectrometers typically use bulky dispersive elements to disperse unknown spectra of varying wavelengths onto detectors with different channels for spectral measurement. This approach requires a sufficient number of channels to achieve ideal spectral measurement accuracy, resulting in the large size of traditional spectrometers. With the widespread adoption of the Internet of Things and intelligent devices, traditional spectrometers are no longer sufficient to meet the rapidly growing demand for compact, small, and low-cost spectral analysis.

[0003] The emergence of computational spectrometers has made up for the shortcomings of traditional spectrometers. The basic principle of computational spectrometers is to input the spectrum to be measured into multiple pre-calibrated optical filters. Multiple optical filters with different transmission characteristics sample the signal to be measured respectively. The optical signal is then converted into an electrical signal by a photodetector to measure the intensity of the filtered signal. Finally, the spectrum is reconstructed by solving the inverse problem. The performance of the computational spectrometer is highly dependent on the optical filter used. The number of sampling channels required for the computational spectrometer can be much smaller than the number of sampling points within a certain bandwidth. Therefore, the computational spectrometer can maintain a small size while maintaining high measurement accuracy, making it more suitable for today's high-precision measurement of spectra and the demand for miniaturization of spectrometers.

[0004] The optical filtering devices currently used in computational spectrometers can be divided into passive devices and active devices. Passive devices expand the number of filtering channels through a series of spectroscopic devices, such as directional couplers, multimode interference couplers (MMI) and other devices. The introduction of the spectroscopic device reduces the dynamic range of the spectrometer, increases the floor space of the spectrometer and reduces the integration. The above defects limit the application scenarios of this type of computational spectrometer. For active devices, they often have only one filtering channel, and require thermo-optical modulation or electro-optical modulation to expand the filtering channel in the time domain, which increases the complexity of operation. In addition, current computational spectrometers can often only reconstruct a single mode of light (TE or TM), so for computational spectrometers, improving their dynamic range and integration and reducing their operational complexity while enabling them to reconstruct multiple modes of light has become an urgent problem to be solved. Summary of the Invention

[0005] In response to the above-mentioned deficiencies in the prior art, the present invention provides an optical filtering device, a computational spectrometer, and a spectrum reconstruction method, which solve the problems of current computational spectrometers, such as low dynamic range, large footprint, complex operation, and single working mode.

[0006] To achieve the above object, the technical solution adopted by the present invention is:

[0007] In a first aspect, an optical filtering device is provided, comprising a multi-microring resonator parallel structure formed by cascading a plurality of uplink and downlink microring resonators, each of which is provided with an adjustable phase shifter; an input port, wherein the input port separates TE light and TM light through a polarization beam splitter and is respectively connected to one end of an upper and lower waveguide of the multi-microring resonator parallel structure, and the other ends of the upper and lower waveguides each independently output TE light and TM light through a polarization beam splitter.

[0008] Furthermore, the resonant cavity in the up-down-down microring resonator is a closed structure connected end to end.

[0009] Furthermore, the adjustable phase shifter is arranged in the resonant cavity of the up-downlink microring resonator and the straight waveguide connecting the up-downlink microring resonators.

[0010] Furthermore, each parallel branch of the multi-microring resonator parallel structure includes one uplink-downlink microring resonator or multiple uplink-downlink microring resonators connected in series.

[0011] In the second aspect, a computational spectrometer is provided, which includes an optical filtering device, a light source and a photodetector, wherein the optical filtering device expands the number of filtering channels by time domain phase modulation. N The calculation formula is:

[0012] N =2 p n

[0013] in, p is the number of phase states that can be changed by phase modulation of the uplink-downlink microring resonator, n is the number of uplink and downlink microring resonators.

[0014] In a third aspect, a spectrum reconstruction method for a computational spectrometer is provided, comprising the following steps:

[0015] S1: The broadband light source is separated into TE light and TM light by a polarization beam splitter, and the two are inputted through the corresponding input ports respectively, and the filtering characteristics are characterized by the optical filtering device respectively;

[0016] S2: TE light and TM light are separated by polarization beam splitters at the output end and sampled by corresponding photodetectors to obtain corresponding output power values;

[0017] S3: TE light and TM light are spectrally reconstructed based on the corresponding filtering characteristics and output power values.

[0018] Furthermore, before executing step S1, the structural parameters of the optical filter device are adjusted by an inverse design algorithm, and the adjustment method is as follows:

[0019] A1: Initialize the structural parameters of the optical filter device, including the circumference of the resonant cavity in the uplink-downlink microring resonator, the coupling coefficient between the resonant cavity and the upper and lower waveguides, and the spacing between the uplink-downlink microring resonators.

[0020] A2: Calculate the autocorrelation width of the filter spectrum of the optical filter device;

[0021] A3: Randomly iterate the structural parameters of the optical filter device and recalculate the autocorrelation width of the filter spectrum line;

[0022] A4: If the autocorrelation width after the structural parameter iteration is smaller than the autocorrelation width before the structural parameter iteration, then execute step A5; otherwise, execute step A6;

[0023] A5: Keep the structural parameters after iteration and return to step A3;

[0024] A6: Retain the structural parameters before iteration and determine whether the number of iterations reaches the set threshold. If not, return to step A3; if so, output the corresponding structural parameters.

[0025] The beneficial effects of the present invention are:

[0026] 1. The optical filter device in this scheme has a large number of adjustable structural parameters, and an inverse design algorithm is used to adjust the structural parameters of the optical filter device, making its spectral transmission line more random, thereby achieving the ideal autocorrelation width. The optical filter has two filtering channels, achieving the effect of one input and two outputs. Under the same scanning time, the number of filtering channels of the optical filter device can be doubled. The optical filter device can reconstruct TE light and TM light simultaneously, or reconstruct TE light and TM light separately.

[0027] 2. The resonant cavity in the up-down microring resonator is a closed structure connected end to end, which can make the coupling area lengths of the resonant cavity and the upper and lower waveguides different. By changing the coupling length, the coupling coefficient can be changed, thereby achieving a larger range of coupling coefficient variation.

[0028] 3. Each uplink-downlink microring resonator is equipped with an adjustable phase shifter, and the effective refractive index of the microring resonator can be changed by the adjustable phase shifter, so that the filtering device exhibits different spectral characteristics in the time domain, thereby expanding the number of filtering channels in the time domain. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a schematic diagram of the structure of the optical filtering device of this scheme.

[0030] Figure 2 This is a schematic diagram of the structure of the expanded optical filtering device of this scheme.

[0031] Figure 3 This is a flow chart for adjusting the structural parameters of the optical filter device.

[0032] Figure 4 It is the filtering curve diagram under different phase states.

[0033] Figure 5 This is a test chart for the reconstruction of broadband spectral signals by a computational spectrometer.

[0034] Figure 6 This is a test chart for the reconstruction of narrowband spectral signals by computational spectrometer.

[0035] Among them, 1. Up-down loading microring resonator, 2. adjustable phase shifter, 3. polarization beam splitter. DETAILED DESCRIPTION

[0036] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0037] like Figure 1 As shown, the optical filtering device of this scheme includes a multi-microring resonator parallel structure formed by cascading several uplink and downlink microring resonators 1; an input port, which separates TE light and TM light through a polarization beam splitter 3 and is respectively connected to one end of the upper and lower waveguides of the multi-microring resonator parallel structure, and the other ends of the upper and lower waveguides both output TE light and TM light independently through the polarization beam splitter 3, and then reconstruct the spectra of the TE light and TM light respectively.

[0038] Each up-download microring resonator 1 has an adjustable phase shifter 2 in its resonant cavity. The resonance equation satisfied by the up-download microring resonator 1 is:

[0039]

[0040] in, λ represents the resonant wavelength, R is the microannulus radius, n c represents the effective refractive index, mis the resonance order (positive integer); the effective refractive index of the uplink and downlink microring resonator 1 can be changed by the adjustable phase shifter 2, so that the filtering device exhibits different spectral characteristics in the time domain, thereby expanding the number of filtering channels in the time domain.

[0041] Assume that the number of uplink and downlink microring resonators 1 is n The adjustable phase shifter 2 can change the phase state of each uplink and downlink microring resonator 1 by phase modulation. p , then the number of filter channels that can be expanded in the time domain for a physical channel is p n For the present invention, the filtering device has two physical channels, the through end and the download end, so the filter channel can be expanded in the time domain. N ,satisfy N =2 p n .

[0042] The structural parameters of the optical filtering device include the circumference of the resonant cavity in the uplink-downlink microring resonator 1, the coupling coefficient between the resonant cavity and the upper and lower waveguides, and the spacing d1 between the uplink-downlink microring resonators 1. The circumference of the resonant cavity, the coupling coefficient between the resonant cavity and the upper and lower waveguides, and the spacing between the uplink-downlink microring resonators 1 in each uplink-downlink microring resonator 1 are different. Assuming that the number of microring resonators is n(n> 1 ) , then the number of adjustable parameters of the entire optical filtering device is 4n- 1.

[0043] The up-down microring resonator 1 changes the coupling coefficient by changing the coupling lengths L1 and L2, thereby achieving a larger range of coupling coefficient variation. Therefore, the length of the coupling region between the resonant cavity and the upper and lower waveguides in each up-down microring resonator 1 is different, and the resonant cavity is a closed structure connected end to end; at the same time, the upper and lower waveguides can be designed as a combination of straight waveguides and curved waveguides, so that the circumference of the up-down microring resonator 1 has a larger range of variation.

[0044] like Figure 2 As shown, each parallel branch of the multi-microring resonator parallel structure can be expanded into two up-down-down microring resonators 1 connected in series.

[0045] like Figure 3 As shown, this scheme adjusts the structural parameters of the optical filter device through the inverse design algorithm to make its spectral transmission line more random, so as to achieve the ideal autocorrelation width. The adjustment method is:

[0046] A1: Initialize the structural parameters of the optical filter device, including the circumference of the resonant cavity in the uplink-downlink microring resonator 1, the coupling coefficient between the resonant cavity and the upper and lower waveguides, and the spacing between the uplink-downlink microring resonators 1;

[0047] A2: Calculate the autocorrelation width of the optical filter device's filter spectrum line using the autocorrelation function. The calculation formula for the autocorrelation function is:

[0048]

[0049] in, is the intensity of the transmission spectrum, <...> λ To find the average value within a specific band, is the wavelength shift, The full width at half maximum (HWHM) is the autocorrelation width;

[0050] A3: Randomly iterate the structural parameters of the optical filter device and recalculate the autocorrelation width of the filter spectrum line;

[0051] A4: If the autocorrelation width after the structural parameter iteration is smaller than the autocorrelation width before the structural parameter iteration, then execute step A5; otherwise, execute step A6;

[0052] A5: Keep the structural parameters after iteration and return to step A3;

[0053] A6: Retain the structural parameters before iteration and determine whether the number of iterations reaches the set threshold. If not, return to step A3; if so, output the corresponding structural parameters.

[0054] This solution also provides a computational spectrometer, which includes an optical filtering device, a light source and a photodetector.

[0055] In specific implementation, the optical filtering device and the detector array can be a monolithic integrated chip, manufactured through compatible processes on a common substrate material; the two can also be implemented separately by independent chips and integrated into a system through packaging. The preparation and processing technology is compatible with the widely used CMOS process, making the overall processing difficulty of the device lower; at the same time, the device itself has low loss and large working bandwidth, which can further improve the practicality of the computational spectrometer.

[0056] The spectrum reconstruction method of the computational spectrometer in this scheme includes the following steps:

[0057] S1: The broadband light source is separated into TE light and TM light by the polarization beam splitter 3, and the two are inputted through the corresponding input ports respectively, and the filtering characteristics are characterized by the optical filtering device respectively;

[0058] S2: TE light and TM light are separated by polarization beam splitter 3 at the output end and sampled by corresponding photodetectors to obtain corresponding output power values;

[0059] S3: TE light and TM light are spectrally reconstructed based on the corresponding filtering characteristics and output power values.

[0060] In this scheme, the unknown spectrum is sampled by the optical filtering device and then converted into an electrical signal through a photodetector array. Finally, the unknown spectrum can be reconstructed through related algorithms such as compressed sensing, truncated inversion, and deep learning.

[0061] In order to verify the autocorrelation of the filtering spectrum of the optical filtering device and the cross-correlation of the filtering spectrum between different filtering channels, it is assumed that the optical filtering device is composed of six cascaded upstream and downstream microring resonators 1. In actual applications, the number can be adjusted at will. It is assumed that each upstream and downstream microring resonator 1 has two phase states of 0 and π. According to the previous discussion, a total of 128 groups of filtering channels can be generated at the through end and the downstream end; the above optical filtering device is simulated and calculated in Matlab using the scattering matrix method. The microring radius varies between 15-40 microns, the coupling coefficient varies between 0.2-0.85, and the microring spacing varies between 150-300um to avoid thermal crosstalk as much as possible.

[0062] like Figure 4 As shown in the figure, it shows the spectral responses of two filter channels randomly selected from 128 filter channels; observing the waveforms, it can be seen that the randomness of each waveform itself is relatively large, that is, the autocorrelation is relatively small, and the calculated autocorrelation width is 0.15; at the same time, the difference between the two waveforms is relatively large, that is, the cross-correlation is relatively small.

[0063] According to the above analysis, by changing the circumference of each up-down microring resonator 1 in the optical filtering device proposed in this scheme, the coupling coefficient between the up-down microring resonator 1 and the upper and lower waveguides, and the spacing between the up-down microring resonators 1, the transmission spectrum of the device itself can be changed, thereby ensuring that the randomness of the transmission spectrum of each device itself is relatively large. The autocorrelation width is calculated to be 0.15, and the transmission spectra between different devices are relatively different and the mutual correlation is relatively small, so that the optical filtering device meets the requirements for the design of a computational spectrometer.

[0064] In this scheme, the spectrum to be measured in a single mode (TE or TM) is divided into two paths, the straight-through end and the download end, after passing through the optical filter device. The number of filtering channels can be expanded in the time domain by the adjustable phase shifter 2. Assuming that the number of sampling points within the working bandwidth is M , then the number of filter channels N Can be much smaller than the number of sampling points M ; The spectrum to be measured passes NAfter sampling in the filter channel, the photodetector performs photoelectric conversion on the collected light signal and converts it into an electrical signal. Its output power value can be expressed as:

[0065] ;

[0066]

[0067] in, is the transmission matrix after N-way sampling; For the i The transmission spectrum of the optical signal, i =1,2,……,N; To pass N Output power value after sampling of the filtering channel; is an unknown spectral signal with M sampling numbers.

[0068] By solving the above non-homogeneous linear equations, the unknown spectral signal can be reconstructed. The number of equations is much smaller than the number of unknowns. This is the advantage of computational spectrometers over traditional spectrometers.

[0069] The computational spectrometer is numerically simulated in Matlab. Six up-down microring resonators 1 are used. Each up-down microring resonator 1 has two phase states, and the number of filter channels generated is 128. The spectrum of the wide-band signal and the narrow-band signal is reconstructed separately, as shown in the following example: Figure 5 As shown, it shows the result of reconstructing the wide spectrum signal; Figure 6 As shown in the figure, it shows the reconstruction results of two narrow-band signals with a spacing difference of 20pm; the reconstructed spectrum is basically completely consistent with the actual spectrum, and the spectral resolution can reach 20pm. The computational spectrometer demonstrated has doubled the number of filter channels produced by a single-channel spectrometer at the same sampling time, and the spectral resolution achieved is far superior to that of ordinary computational spectrometers.

Claims

1. An optical filtering device, characterized in that: include: A multi-microring resonator parallel structure formed by cascading several up-downlink microring resonators, and each up-downlink microring resonator is provided with an adjustable phase shifter; An input port, wherein the input port separates TE light and TM light through a polarization beam splitter and is respectively connected to one end of the upper and lower waveguides of the multi-microring resonator parallel structure, and the other ends of the upper and lower waveguides each output TE light and TM light independently through the polarization beam splitter; The resonant cavity in the up-down-down microring resonator is a closed structure connected end to end; The adjustable phase shifter is arranged in the resonant cavity of the up-downlink microring resonator and the straight waveguide connecting the up-downlink microring resonator; Each parallel branch of the multi-microring resonator parallel structure includes one up-down-down type microring resonator or multiple up-down-down type microring resonators connected in series.

2. A computational spectrometer, characterized in that The optical filter device comprises the optical filter device according to claim 1, a light source and a photodetector, wherein the optical filter device expands the number of filtering channels by time domain phase modulation. N The calculation formula is: N =2 p n in, p is the number of phase states that can be changed by phase modulation of the uplink-downlink microring resonator, n is the number of uplink and downlink microring resonators.

3. A spectrum reconstruction method using the computational spectrometer according to claim 2, characterized in that: The following steps are involved: S1: The broadband light source is separated into TE light and TM light by a polarization beam splitter, and the two are inputted through the corresponding input ports respectively, and the filtering characteristics are characterized by the optical filtering device respectively; S2: TE light and TM light are separated by polarization beam splitters at the output end and sampled by corresponding photodetectors to obtain corresponding output power values; S3: TE light and TM light are spectrally reconstructed based on the corresponding filtering characteristics and output power values; Before executing step S1, the structural parameters of the optical filter device are adjusted by an inverse design algorithm, and the adjustment method is as follows: A1: Initialize the structural parameters of the optical filter device, including the circumference of the resonant cavity in the uplink-downlink microring resonator, the coupling coefficient between the resonant cavity and the upper and lower waveguides, and the spacing between the uplink-downlink microring resonators. A2: Calculate the autocorrelation width of the optical filter device’s filter spectrum line through the autocorrelation function; A3: Randomly iterate the structural parameters of the optical filter device and recalculate the autocorrelation width of the filter spectrum line; A4: If the autocorrelation width after the structural parameter iteration is smaller than the autocorrelation width before the structural parameter iteration, then execute step A5; otherwise, execute step A6; A5: Keep the structural parameters after iteration and return to step A3; A6: Retain the structural parameters before iteration and determine whether the number of iterations reaches the set threshold. If not, return to step A3; if so, output the corresponding structural parameters.

4. The spectrum reconstruction method of the computational spectrometer according to claim 3, characterized in that: The calculation formula of the autocorrelation function is: in, is the intensity of the transmission spectrum, <...> λ To find the average value within a specific band, is the wavelength shift, The full width at half maximum is the autocorrelation width.

5. The spectrum reconstruction method of the computational spectrometer according to claim 3, characterized in that: The formula for calculating the output power value is: ； in, is the transmission matrix after N-way sampling; For the i The transmission spectrum of the optical signal, i =1,2,……,N; To pass N Output power value after sampling of the filtering channel; is an unknown spectral signal with M sampling numbers; By solving , the unknown spectral signal can be reconstructed.

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