Patent Application
20230099485
This disclosure relates generally to photonic devices, and in particular but not exclusively, relates to optical multiplexers and demultiplexers.
Fiber-optic communication is typically employed to transmit information from one place to another via light that has been modulated to carry the information. For example, many telecommunication companies use optical fiber to transmit telephone signals, internet communication, and cable television signals. But the cost of deploying optical fibers for fiber-optic communication may be prohibitive. As such, techniques have been developed to more efficiently use the bandwidth available within a single optical fiber. Wavelength-division multiplexing is one such technique that bundles multiple optical carrier signals onto a single optical fiber using different wavelengths.
In some embodiments, a non-transitory computer-readable medium is provided. The computer-readable medium has logic stored thereon that, in response to execution by one or more processors of a computing system, causes the computing system to perform actions for creating a design for a physical device. The actions include receiving, by the computing system, an initial design of the physical device; simulating performance of the physical device using the initial design; determining a performance loss value for the physical device based on the simulated performance at a target wavelength and one or more delta wavelengths; backpropagating the performance loss value to determine a gradient corresponding to an influence of changes in the initial design on the total performance loss value; and revising the initial design of the physical device based at least in part on the gradient.
In some embodiments, a system is provided. The system includes a photonic device and one or more temperature management devices. The photonic device is fabricated based on a design that is determined using an inverse design process that includes determining a performance loss value based on simulated performance at a target wavelength and one or more delta wavelengths. The one or more temperature management devices are configured to adjust an operating temperature of the photonic device to achieve a maximum performance at the target wavelength.
Non-limiting and non-exhaustive embodiments of the invention are described with reference to the following figures, wherein like reference numerals refer to like parts throughout the various views unless otherwise specified. Not all instances of an element are necessarily labeled so as not to clutter the drawings where appropriate. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles being described. To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced.
Embodiments of techniques for inverse design of physical devices are described herein, in the context of generating designs for photonic integrated circuits (including a multi-channel photonic demultiplexer). In the following description numerous specific details are set forth to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the techniques described herein can be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring certain aspects.
Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Wavelength division multiplexing and its variants (e.g., dense wavelength division multiplexing, coarse wavelength division multiplexing, and the like) take advantage of the bandwidth of optical fibers by bundling multiple optical carrier signals onto a single optical fiber. Once the multiple carrier signals are bundled together, they are transmitted from one place to another over the single optical fiber where they may be demultiplexed to be read out by an optical communication device. However, devices that decouple the carrier signals from one another remain prohibitive in terms of cost, size, and the like.
Moreover, design of photonic devices, such as those used for optical communication, are traditionally designed via conventional techniques sometimes determined through a simple guess and check method or manually-guided grid-search in which a small number of design parameters from pre-determined designs or building blocks are adjusted for suitability to a particular application. However, in actuality, these devices may have design parameters ranging from hundreds all the way to many billions or more, dependent on the device size and functionality. Thus, as functionality of photonic devices increases and manufacturing tolerances improve to allow for smaller device feature sizes, it becomes increasingly important to take full advantage of these improvements via optimized device design.
Described herein are embodiments of a photonic integrated circuit (e.g., a multi-channel photonic demultiplexer and/or multiplexer) having a design obtainable by an inverse design process. More specifically, techniques described in embodiments herein utilize gradient-based optimization in combination with first-principle simulations to generate a design from an understanding of the underlying physics that are expected to govern the operation of the photonic integrated circuit. It is appreciated in other embodiments, design optimization of photonic integrated circuits without gradient-based techniques may also be used. Advantageously, embodiments and techniques described herein are not limited to conventional techniques used for design of photonic devices, in which a small number of design parameters for pre-determined building blocks are adjusted based on suitability to a particular application. Rather, the first-principles based designs described herein are not necessarily dependent on human intuition and generally may result in designs which outstrip current state-of-the-art designs in performance, size, robustness, or a combination thereof. Further still, rather than being limited to a small number of design parameters due to conventional techniques, the embodiments and techniques described herein may provide scalable optimization of a nearly unlimited number of design parameters. It will also be appreciated that, though the design and fabrication of photonic integrated circuits is described throughout the present text, similar inverse design techniques may be used to generate designs for other types of physical devices.
In the illustrated embodiment, optical communication device 102 includes a controller 104, one or more interface device(s) 112 (e.g., fiber optic couplers, light guides, waveguides, and the like), a multiplexer (mux), demultiplexer (demux), or combination thereof (MUX/DEMUX 114), one or more light source(s) 116 (e.g., light emitting diodes, lasers, and the like), and one or more light sensor(s) 118 (e.g., photodiodes, phototransistors, photoresistors, and the like) coupled to one another. The controller includes one or more processor(s) 106 (e.g., one or more central processing units, application specific circuits, field programmable gate arrays, or otherwise) and memory 108 (e.g., volatile memory such as DRAM and SAM, non-volatile memory such as ROM, flash memory, and the like). It is appreciated that optical communication device 120 may include the same or similar elements as optical communication device 102, which have been omitted for clarity.
Controller 104 orchestrates operation of optical communication device 102 for transmitting and/or receiving optical signal 110 (e.g., a multi-channel optical signal having a plurality of distinct wavelength channels or otherwise). Controller 104 includes software (e.g., instructions included in memory 108 coupled to processor 106) and/or hardware logic (e.g., application specific integrated circuits, field-programmable gate arrays, and the like) that when executed by controller 104 causes controller 104 and/or optical communication device 102 to perform operations.
In one embodiment, controller 104 may choreograph operations of optical communication device 102 to cause light source(s) 116 to generate a plurality of distinct wavelength channels that are multiplexed via MUX/DEMUX 114 into a multi-channel optical signal 110 that is subsequently transmitted to optical communication device 120 via interface device 112. In other words, light source(s) 116 may output light having different wavelengths (e.g., 1271 nm, 1291 nm, 1311 nm, 1331 nm, 1506 nm, 1514 nm, 1551 nm, 1571, or otherwise) that may be modulated or pulsed via controller 104 to generate a plurality of distinct wavelength channels representative of information. The plurality of distinct wavelength channels are subsequently combined or otherwise multiplexed via MUX/DEMUX 114 into a multi-channel optical signal 110 that is transmitted to optical communication device 120 via interface device 112. In the same or another embodiment, controller 104 may choreograph operations of optical communication device 102 to cause a plurality of distinct wavelength channels to be demultiplexed via MUX/DEMUX 114 from a multi-channel optical signal 110 that is received via interface device 112 from optical communication device 120.
It is appreciated that in some embodiments certain elements of optical communication device 102 and/or optical communication device 120 may have been omitted to avoid obscuring certain aspects of the disclosure. For example, optical communication device 102 and optical communication device 120 may include amplification circuitry, lenses, or components to facilitate transmitting and receiving optical signal 110. It is further appreciated that in some embodiments optical communication device 102 and/or optical communication device 120 may not necessarily include all elements illustrated in
As illustrated in
In the illustrated embodiment of
As illustrated in
In the illustrated embodiment each of the plurality of output regions 304 are parallel to each other one of the plurality of output regions 304. However, in other embodiments the plurality of output regions 304 may not be parallel to one another or even disposed on the same side (e.g., one or more of the plurality of output regions 304 and/or input region 302 may be disposed proximate to sides of dispersive region 332 that are adjacent to first side 328 and/or second side 330). In some embodiments adjacent ones of the plurality of output regions are separated from each other by a common separation distance when the plurality of output regions includes at least three output regions. For example, as illustrated adjacent output region 308 and output region 310 are separated from one another by distance 306, which may be common to the separation distance between other pairs of adjacent output regions.
As illustrated in the embodiment of
It is noted that the first material and second material of dispersive region 332 are arranged and shaped within the dispersive region such that the material interface pattern is substantially proportional to a design obtainable with an inverse design process, which will be discussed in greater detail later in the present disclosure. More specifically, in some embodiments, the inverse design process may include iterative gradient-based optimization of a design based at least in part on a loss function that incorporates a performance loss (e.g., to enforce functionality) and a fabrication loss (e.g., to enforce fabricability and binarization of a first material and a second material) that is reduced or otherwise adjusted via iterative gradient-based optimization to generate the design. In the same or other embodiment, other optimization techniques may be used instead of, or jointly with, gradient-based optimization. Advantageously, this allows for optimization of a near unlimited number of design parameters to achieve functionality and performance within a predetermined area that may not have been possible with conventional design techniques.
For example, in one embodiment dispersive region 332 is structured to optically separate each of the four channels from the multi-channel optical signal within a predetermined area of 35 μm×35 μm (e.g., as defined by width 324 and length 326 of dispersive region 332) when the input region 302 receives the multi-channel optical signal. In the same or another embodiment, the dispersive region is structured to accommodate a common bandwidth for each of the four channels, each of the four channels having different center wavelengths. In one embodiment the common bandwidth is approximately 13 nm wide and the different center wavelengths is selected from a group consisting of 1271 nm, 1291 nm, 1311 nm, 1331 nm, 1506 nm, 1514 nm, 1551 nm, and 1571 nm. In some embodiments, the entire structure of demultiplexer 316 (e.g., including input region 302, periphery region 318, dispersive region 332, and plurality of output regions 304) fits within a predetermined area (e.g., as defined by width 320 and length 322). In one embodiment the predetermined area is 35 μm×35 μm. It is appreciated that in other embodiments dispersive region 332 and/or demultiplexer 316 fits within other areas greater than or less than 35 μm×35 μm, which may result in changes to the structure of dispersive region 332 (e.g., the arrangement and shape of the first and second material) and/or other components of demultiplexer 316.
In the same or other embodiments the dispersive region is structured to have a power transmission of −2 dB or greater from the input region 302, through the dispersive region 332, and to the corresponding one of the plurality of output regions 304 for a given wavelength within one of the plurality of distinct wavelength channels. For example, if channel 1 of a multi-channel optical signal is mapped to output region 308, then when demultiplexer 316 receives the multi-channel optical signal at input region 302 the dispersive region 332 will optically separate channel 1 from the multi-channel optical signal and guide a portion of the multi-channel optical signal corresponding to channel 1 to output region 308 with a power transmission of −2 dB or greater. In the same or another embodiment, dispersive region 332 is structured such that an adverse power transmission (i.e., isolation) for the given wavelength from the input region to any of the plurality of output regions other than the corresponding one of the plurality of output regions is −30 dB or less, −22 dB or less, or otherwise. For example, if channel 1 of a multi-channel optical signal is mapped to output region 308, then the adverse power transmission from input region 302 to any other one of the plurality of output regions (e.g., output region 310, output region 312, output region 314) other than the corresponding one of the plurality of output regions (e.g., output region 308) is −30 dB or less, −22 dB or less, or otherwise. In some embodiments, a maximum power reflection from demultiplexer 316 of an input signal (e.g., a multi-channel optical signal) received at an input region (e.g., input region 302) is reflected back to the input region by dispersive region 332 or otherwise is −40 dB or less, −20 dB or less, −8 dB or less, or otherwise. It is appreciated that in other embodiments the power transmission, adverse power transmission, maximum power, or other performance characteristics may be different than the respective values discussed herein, but the structure of dispersive region 332 may change due to the intrinsic relationship between structure, functionality, and performance of demultiplexer 316.
In one embodiment a silicon on insulator (SOI) wafer may be initially provided that includes a support substrate (e.g., a silicon substrate) that corresponds to substrate 334, a silicon dioxide dielectric layer that corresponds to dielectric layer 336, a silicon layer (e.g., intrinsic, doped, or otherwise), and a oxide layer (e.g., intrinsic, grown, or otherwise). In one embodiment, the silicon in the active layer 338 may be etched selectively by lithographically creating a pattern on the SOI wafer that is transferred to SOI wafer via a dry etch process (e.g., via a photoresist mask or other hard mask) to remove portions of the silicon. The silicon may be etched all the way down to dielectric layer 336 to form voids that may subsequently be backfilled with silicon dioxide that is subsequently encapsulated with silicon dioxide to form cladding layer 340. In one embodiment, there may be several etch depths including a full etch depth of the silicon to obtain the targeted structure. In one embodiment, the silicon may be 206 nm thick and thus the full etch depth may be 206 nm. In some embodiments, this may be a two-step encapsulation process in which two silicon dioxide depositions are performed with an intermediate chemical mechanical planarization used to yield a planar surface.
It is appreciated that in the illustrated embodiments of demultiplexer 316 as shown in
As illustrated in
The first material 410 (i.e., black colored regions within dispersive region 406) and second material 412 (i.e., white colored regions within dispersive region 406) of photonic demultiplexer 400 are inhomogeneously interspersed to create a plurality of interfaces that collectively form material interface pattern 420 as illustrated in
As illustrated in
In some embodiments, material interface pattern 420 includes one or more dendritic shapes, wherein each of the one or more dendritic shapes are defined as a branched structure formed from first material 410 or second material 412 and having a width that alternates between increasing and decreasing in size along a corresponding direction. Referring back to
In some embodiments, the inverse design process includes a fabrication loss that enforces a minimum feature size, for example, to ensure fabricability of the design. In the illustrated embodiment of photonic demultiplexer 400 illustrated in
As illustrated, system 500 includes controller 512, display 502, input device(s) 504, communication device(s) 506, network 508, remote resources 510, bus 534, and bus 520. Controller 512 includes processor 514, memory 516, local storage 518, and photonic device simulator 522. Photonic device simulator 522 includes operational simulation engine 526, fabrication loss calculation logic 528, calculation logic 524, adjoint simulation engine 530, and optimization engine 532. It is appreciated that in some embodiments, controller 512 may be a distributed system.
Controller 512 is coupled to display 502 (e.g., a light emitting diode display, a liquid crystal display, and the like) coupled to bus 534 through bus 520 for displaying information to a user utilizing system 500 to optimize structural parameters of the photonic device (i.e., demultiplexer). Input device 504 is coupled to bus 534 through bus 520 for communicating information and command selections to processor 514. Input device 504 may include a mouse, trackball, keyboard, stylus, or other computer peripheral, to facilitate an interaction between the user and controller 512. In response, controller 512 may provide verification of the interaction through display 502.
Another device, which may optionally be coupled to controller 512, is a communication device 506 for accessing remote resources 510 of a distributed system via network 508. Communication device 506 may include any of a number of networking peripheral devices such as those used for coupling to an Ethernet, Internet, or wide area network, and the like. Communication device 506 may further include a mechanism that provides connectivity between controller 512 and the outside world. Note that any or all of the components of system 500 illustrated in
Controller 512 orchestrates operation of system 500 for optimizing structural parameters of the photonic device. Processor 514 (e.g., one or more central processing units, graphics processing units, and/or tensor processing units, etc.), memory 516 (e.g., volatile memory such as DRAM and SRAM, non-volatile memory such as ROM, flash memory, and the like), local storage 518 (e.g., magnetic memory such as computer disk drives), and the photonic device simulator 522 are coupled to each other through bus 520. Controller 512 includes software (e.g., instructions included in memory 516 coupled to processor 514) and/or hardware logic (e.g., application specific integrated circuits, field-programmable gate arrays, and the like) that when executed by controller 512 causes controller 512 or system 500 to perform operations. The operations may be based on instructions stored within any one of, or a combination of, memory 516, local storage 518, physical device simulator 522, and remote resources 510 accessed through network 508.
In the illustrated embodiment, the components of photonic device simulator 522 are utilized to optimize structural parameters of the photonic device (e.g., MUX/DEMUX 114 of
As illustrated in
Each of the plurality of voxels 612 may be associated with a structural value, a field value, and a source value. Collectively, the structural values of the simulated environment 606 describe the structural parameters of the photonic device. In one embodiment, the structural values may correspond to a relative permittivity, permeability, and/or refractive index that collectively describe structural (i.e., material) boundaries or interfaces of the photonic device (e.g., material interface pattern 420 of
In the illustrated embodiment, the photonic device corresponds to an optical demultiplexer having a design region 614 (e.g., corresponding to dispersive region 332 of
However, in other embodiments, the entirety of the photonic device may be placed within the design region 614 such that the structural parameters may represent any portion or the entirety of the design of the photonic device. The electric and magnetic fields within the simulated environment 606 (and subsequently the photonic device) may change (e.g., represented by field values of the individual voxels that collectively correspond to the field response of the simulated environment) in response to the excitation source. The output ports 604 of the optical demultiplexer may be used for determining a performance metric of the photonic device in response to the excitation source (e.g., power transmission from input port 602 to a specific one of the output ports 604). The initial description of the photonic device, including initial structural parameters, excitation source, performance parameters or metrics, and other parameters describing the photonic device, are received by the system (e.g., system 500 of
Once the operational simulation reaches a steady state (e.g., changes to the field values in response to the excitation source substantially stabilize or reduce to negligible values) or otherwise concludes, one or more performance metrics may be determined. In one embodiment, the performance metric corresponds to the power transmission at a corresponding one of the output ports 604 mapped to the distinct wavelength channel being simulated by the excitation source. In other words, in some embodiments, the performance metric represents power (at one or more frequencies of interest) in the target mode shape at the specific locations of the output ports 604. A loss value or metric of the input design (e.g., the initial design and/or any refined design in which the structural parameters have been updated) based, at least in part, on the performance metric may be determined via a loss function. The loss metric, in conjunction with an adjoint simulation, may be utilized to determine a structural gradient (e.g., influence of structural parameters on loss metric) for updating or otherwise revising the structural parameters to reduce the loss metric (i.e. increase the performance metric). It is noted that the loss metric may be further based on a fabrication loss value that is utilized to enforce a minimum feature size of the photonic device to promote fabricability of the device, and/or other loss values.
In some embodiments, iterative cycles of performing the operational simulation, and adjoint simulation, determining the structural gradient, and updating the structural parameters to reduce the loss metric are performed successively as part of an inverse design process that utilizes iterative gradient-based optimization. An optimization scheme such as gradient descent may be utilized to determine specific amounts or degrees of changes to the structural parameters of the photonic device to incrementally reduce the loss metric. More specifically, after each cycle the structural parameters are updated (e.g., optimized) to reduce the loss metric. The operational simulation, adjoint simulation, and updating the structural parameters are iteratively repeated until the loss metric substantially converges or is otherwise below or within a threshold value or range such that the photonic device provides the desired performed while maintaining fabricability.
One problem in designing physical devices such as the photonic devices described above is that, even if a simulated photonic device is designed that is highly performant, physical realities of manufacturing the designed photonic device may reduce the actual performance of the photonic device as manufactured. For example, differences in operating conditions for a fabrication system, including but not limited to an ambient temperature, a surface roughness of a material to be processed, other material imperfections of a material to be processed, misalignment of the fabrication system, waveguide thickness, structure out of plane, sidewall angle, and optical aberrations within the fabrication system, may cause differences to be introduced between the structure of the physical device as designed and the structure of the physical device as manufactured, including but not limited to erosion and dilation of features of the photonic device. That is, the different operating conditions may cause the features of the physical device to be smaller, larger, or differently shaped than the design that is provided to the fabrication system. What is desired are design techniques that will result in designs for physical devices that are highly performant and are also robust to changes in operating conditions of the fabrication system.
It has been found that the differences in operating conditions tend to introduce shifts in performance such as these, but do not significantly otherwise change the shape of the performance curve. Importantly, changes in operating temperature from a nominal temperature have also been found to produce similar wavelength performance shifts. Taking these findings together, it has been discovered that a performance curve for a photonic device that has been shifted away from a nominal performance due to differences in operating conditions during fabrication can be shifted back to the desired performance during operation by altering the operating temperature.
Through the discovery that the performance of photonic devices that depart from a nominal design due to manufacturing irregularities can be tuned using different operating temperatures to match that of a nominal photonic device, improvements can be made in the inverse design process used for discovering highly performant nominal designs for photonic devices.
In the illustrated embodiment, the operational simulation 802 utilizes a finite-difference time-domain (FDTD) method to model the field response (both electric and magnetic) or loss response at each of a plurality of voxels for a plurality of time steps in response to physical stimuli corresponding to an excitation source and/or adjoint source. The use of an FDTD method should not be seen as limiting, as in other embodiments, other methods (including but not limited to finite-difference frequency-domain (FDFD) methods) may be used in the operational simulation 802 and adjoint simulation 804.
As illustrated in
After receiving the initial design 836, the operational simulation 802 generates a plurality of perturbed structural parameters 806. Each perturbed structural parameter 806 represents the structural parameters of the initial design 836 as they would be fabricated by the fabrication system under a different set of operating conditions. In some embodiments, a fabrication model may be used to simulate the fabrication of the photonic device based on the initial structural parameters and the operating conditions in order to generate the perturbed structural parameters 806.
In some embodiments, the structural parameters of the initial design 836 may be directly perturbed, instead of using a fabrication model to simulate perturbations under different operating conditions. For example, the features represented by the structural parameters may be eroded or dilated directly by a given amount to determine a given set of perturbed structural parameters 806. In such embodiments, the given amount of erosion or dilation may be modified instead of the operating conditions.
In some embodiments, ranges of values for each of the operating conditions may be predetermined. Any suitable technique may then be used to determine the sets of operating conditions for generating the perturbed structural parameters 806. For example, values within the predetermined ranges of values may be stochastically sampled for each of the operating conditions, and combinations of the stochastically sampled values may be used as the sets of operating conditions. As another example, values within the predetermined ranges of values may be uniformly sampled for each operating condition, and combinations of the uniformly sampled values may be used as the sets of operating conditions. As yet another example, a sensitivity for each operating condition may be determined, and then values within the predetermined ranges of values may be sampled in a non-linear manner based on the determined sensitivities. The sensitivities may be determined by analyzing the results obtained with a plurality of sets of operating conditions that vary each operating condition separately.
After the perturbed structural parameters 806 are determined, the operational simulation 802 proceeds to a simulation portion 850, which is performed separately for each of the perturbed structural parameters 806. The simulation portion 850 occurs over a plurality of time-steps (e.g., from an initial time step to a final time step over a pre-determined or conditional number of time steps having a specified time step size) and models changes (e.g., from the initial field values 812) in electric and magnetic fields of a plurality of voxels describing the simulated environment and/or photonic device that collectively correspond to the field response. More specifically, update operations (e.g., update operation 814, update operation 816, and update operation 818) are iterative and based on the field response, structural parameters 808 (that is, for a selected one of the perturbed structural parameters 806), and one or more excitation sources 810. Each update operation is succeeded by another update operation, which are representative of successive steps forward in time within the plurality of time steps. For example, update operation 816 updates the field values 840 (see, e.g.,
Once the final time step of the simulation portion 850 is performed, a performance loss function 820 is used to determine a performance loss value 822 associated with the selected perturbed structural parameter 806. In a naïve implementation, the performance loss function 820 may only consider performance of the simulated photonic device at a target wavelength λ0. However, overall performance of the fabricated photonic device can be improved when considering that a shift of a peak away from the target wavelength λ0 can be shifted back to the target wavelength λ0 by a change of operating temperature for the fabricated photonic device.
Accordingly, in some embodiments, the performance loss function 820 may measure performance at the target wavelength λ0, as well as at one or more delta wavelengths below the target wavelength λ0−x, λ0−2x, and so on to a minimum wavelength λ−d, and/or one or more delta wavelengths above the target wavelength λ0+x, λ0+2x, and so on to a minimum wavelength λd. The performance loss function 820 may then determine the performance loss for the selected perturbed structural parameters 806 based on the performance at the multiple tested wavelengths. For example, in some embodiments, the performance loss function 820 may use a maximum measured performance amongst the multiple tested wavelengths as the performance loss for the selected perturbed structural parameters 806, under the assumption that regardless of the actual tested wavelength, the performance can be shifted to the target wavelength λ0 via a shift in operating temperature.
The delta wavelengths may be chosen using any suitable technique. For example, in some embodiments, a minimum wavelength and a maximum wavelength may be chosen, and the delta wavelengths may be evenly distributed between the minimum wavelength and the maximum wavelength. As another example, in some embodiments, a minimum wavelength and a maximum wavelength may be chosen, and delta wavelengths may be chosen at a finer resolution closer to the target wavelength and at a coarser resolution closer to the minimum wavelength and the maximum wavelength. In some embodiments, only delta wavelengths either above or below the target wavelength may be chosen, instead of both delta wavelengths above and below the target wavelength.
The performance loss values 822 for each of the perturbed structural parameters 806 are then combined into a total performance loss value that can be used to determine (or used as) a loss metric 824. The performance loss values 822 may be combined using any suitable technique. For example, in some embodiments, a linear combination of the performance loss values 822 may be used as the total performance loss value. As another example, in embodiments wherein a non-linear sampling of the operating conditions was performed based on sensitivities associated with each operating condition, a non-linear combination of the performance loss values 822 based on the sensitivities may be performed to create the total performance loss value.
From the loss metric 824, loss gradients may be determined at block 826. The loss gradients determined from block 826 may be treated as adjoint or virtual sources (e.g., physical stimuli or excitation source originating at an output region or port) which are backpropagated in reverse (from the final time step incrementally through the plurality of time steps until reaching the initial time step via update operation 828, update operation 832, and update operation 830) to determine structural gradient 834. Because it is determined based on the total performance loss value, the structural gradient 834 is associated with the initial design 836, as opposed to an individual perturbed structural parameter 806. This allows the initial design 836 to be updated instead of having to individually process each of the perturbed structural parameters 806 and propagate changes in the design back to the initial design 836, thus eliminating a large amount of unnecessary computation.
In the illustrated embodiment, the FDTD solve (e.g., simulation portion 850 of the operational simulation 802) and backward solve (e.g., adjoint simulation 804) problem are described pictorially, from a high-level, using only “update” and “loss” operations as well as their corresponding gradient operations. The simulation is set up initially in which the structural parameters, physical stimuli (i.e., excitation source), and initial field states of the simulated environment (and photonic device) are provided (e.g., via an initial description and/or input design). As discussed previously, the field values are updated in response to the excitation source based on the structural parameters. More specifically, the update operation is given by ϕ, where =ϕ(
,
,
) for
=1, . . . ,
. Here,
corresponds to the total number of time steps (e.g., the plurality of time steps) for the operational simulation, where
corresponds to the field response (the field value associated with the electric and magnetic fields of each of the plurality of voxels) of the simulated environment at time step
,
corresponds to the excitation source(s) (the source value associated with the electric and magnetic fields for each of the plurality of voxels) of the simulated environment at time step
, and
corresponds to the structural parameters describing the topology and/or material properties of the physical device (e.g., relative permittivity, index of refraction, and the like).
It is noted that using the FDTD method, the update operation may specifically be stated as:
ϕ(,
,
)=A(
)
+B(
)
That is to say the FDTD update is linear with respect to the field and source terms. Concretely, A()ε
N×N and B(
)∈
N×N are linear operators which depend on the structure parameters,
, and act on the fields,
, and the sources,
, respectively. Here, it is assumed that
,
,∈
N where N is the number of FDTD field components in the operational simulation. Additionally, the loss operation (e.g., loss function) may be given by L=ƒ(
, . . . ,
), which takes as input the computed fields and produces a single, real-valued scalar (e.g., the loss metric) that can be reduced and/or minimized.
In terms of revising or otherwise optimizing the structural parameters of the physical device, the relevant quantity to produce is
which is used to describe the influence of changes in the structural parameters of the initial design 836 on the loss value and is denoted as the structural gradient 834 illustrated in
which include
The update operation 816 of the operational simulation 802 updates the field values 840, , of the plurality of voxels at the
th time step to the next time step (i.e.,
+1 time step), which correspond to the field values 842,
. The gradients 844 are utilized to determine for the backpropagation (e.g., update operation 832 backwards in time), which combined with the gradients 846 are used, at least in part, to calculate the structural gradient,
is the contribution of each field to the loss metric, L. It is noted that this is the partial derivative, and therefore does not take into account the causal relationship of →
. Thus,
is utilized which encompasses the →
relationship. The loss gradient,
may also be used to compute the structural gradient,
and corresponds to the total derivative of the field with respect to loss value, L. The loss gradient,
at a particular time step, , is equal to the summation of
which corresponds to the field gradient, is used which is the contribution to
from each time/update step.
In particular, the memory footprint to directly compute
is so large that it is difficult to store more than a handful of state Tensors. The state Tensor corresponds to storing the values of all of the FDTD cells (e.g., the plurality of voxels) for a single simulation time step. It is appreciated that the term “tensor” may refer to tensors in a mathematical sense or as described by the TensorFlow framework developed by Alphabet, Inc. In some embodiments the term “tensor” refers to a mathematical tensor which corresponds to a multidimensional array that follows specific transformation laws. However, in most embodiments, the term “tensor” refers to TensorFlow tensors, in which a tensor is described as a generalization of vectors and matrices to potentially higher dimensions (e.g., n-dimensional arrays of base data types), and is not necessarily limited to specific transformation laws. For example, for the general loss function ƒ, it may be necessary to store the fields, , for all time steps,
. This is because, for most choices of ƒ, the gradient will be a function of the arguments of ƒ. This difficulty is compounded by the fact that the values of for larger values of
are needed before the values for smaller
due to the incremental updates of the field response and/or through backpropagation of the loss metric, which may prevent the use of schemes that attempt to store only the values
at an immediate time step.
An additional difficulty is further illustrated when computing the structural gradient,
which is given by:
For completeness, the full form of the first term in the sum,
is expressed as:
Based on the definition of ϕ as described by equation (1), it is noted that
which can be substituted in equation (3) to arrive at an adjoint update for backpropagation (e.g., the update operations such as update operation 832), which can be expressed as:
The adjoint update is the backpropagation of the loss gradient (e.g., from the loss metric) from later to earlier time steps and may be referred to as a backwards solve for
More specifically, the loss gradient may initially be based upon the backpropagation of a loss metric determined from the operational simulation with the loss function. The second term in the sum of the structural gradient,
corresponds to the field gradient and is denoted as:
for the particular form of Φdescribed by the first equation above. Thus, each term of the sum associated depends on both for >=
0 and for
<
0. Since the dependency chains of these two terms are in opposite directions, it is concluded that computing
in this way requires the storage of values for all of
. In some embodiments, the need to store all field values may be mitigated by a reduced representation of the fields.
From a start block, the method 900 proceeds to block 902, where an initial design 836 of a physical device such as a photonic integrated circuit is received. In some embodiments, the physical device may be expected to have a certain functionality (e.g., perform as an optical demultiplexer) after optimization. The initial design 836 may describe structural parameters of the physical device within a simulated environment. The simulated environment may include a plurality of voxels that collectively describe the structural parameters of the physical device. Each of the plurality of voxels is associated with a structural value to describe the structural parameters, a field value to describe the field response (e.g., the electric and magnetic fields in one or more orthogonal directions) to physical stimuli (e.g., one or more excitation sources), and a source value to describe the physical stimuli. In some embodiments the initial design 836 may be a first description of the physical device in which values for the structural parameters may be random values or null values outside of input and output regions such that there is no bias for the initial (e.g., first) design. It is appreciated that the initial description or input design may be a relative term. Thus, in some embodiments an initial description may be a first description of the physical device described within the context of the simulated environment (e.g., a first input design for performing a first operational simulation).
However, in other embodiments, the term initial description may refer to an initial description of a particular cycle (e.g., of performing an operational simulation 802, operating an adjoint simulation 804, and updating the structural parameters). In such an embodiment, the initial design 836 or design of that particular cycle may correspond to a revised description or refined design (e.g., generated from a previous cycle). In some embodiments, the simulated environment includes a design region that includes a portion of the plurality of voxels which have structural parameters that may be updated, revised, or otherwise changed to optimize the structural parameters of the physical device. In the same or other embodiments, the structural parameters are associated with geometric boundaries and/or material compositions of the physical device based on the material properties (e.g., relative permittivity, index of refraction, etc.) of the simulated environment.
At block 904, perturbed structural parameters 806 are generated based on the initial design 836. As discussed above, sets of operating conditions may be generated within the ranges of valid operating conditions using any suitable technique, including but not limited to stochastic sampling, linear sampling, and non-linear sampling based on sensitivities. The sets of operating conditions may then be used to simulate fabrication based on initial structural parameters within the initial design 836 in order to generate the perturbed structural parameters 806.
The method 900 then proceeds to a for-loop defined between a for-loop start block 906 and a for-loop end block 916, wherein each of the perturbed structural parameters 806 is processed. From the for-loop start block 906, the method 900 proceeds to block 908, where a simulated environment is configured to be representative of the perturbed structural parameters of a physical device (e.g., photonic device). Once the perturbed structural parameters have been received or otherwise obtained, the simulated environment is configured (e.g., the number of voxels, shape/arrangement of voxels, and specific values for the structural value, field value, and/or source value of the voxels are set based on the perturbed structural parameters).
In some embodiments the simulated environment includes a design region optically coupled between a first communication region and a plurality of second communication regions. In some embodiments, the first communication region may correspond to an input region or port (e.g., where an excitation source originates), while the second communication may correspond to a plurality of output regions or ports (e.g., when designing an optical demultiplexer that optically separates a plurality of distinct wavelength channels included in a multi-channel optical signal received at the input port and respectively guiding each of the distinct wavelength channels to a corresponding one of the plurality of output ports). However, in other embodiments, the first communication region may correspond to an output region or port, while the plurality of second communication regions corresponds to a plurality of input ports or region (e.g., when designing an optical multiplexer that optically combines a plurality of distinct wavelength signals received at respective ones of the plurality of input ports to form a multi-channel optical signal that is guided to the output port).
Block 910 shows mapping each of a plurality of distinct wavelength channels to a respective one of the plurality of second communication regions. The distinct wavelength channels may be mapped to the second communication regions by virtue of the initial design 836 of the physical device. For example, a loss function may be chosen that associates a performance metric of the physical device with power transmission from the input port to individual output ports for mapped channels. In one embodiment, a first channel included in the plurality of distinct wavelength channels is mapped to a first output port, meaning that the performance metric of the physical device for the first channel is tied to the first output port. Similarly, other output ports may be mapped to the same or different channels included in the plurality of distinct wavelength channels such that each of the distinct wavelength channels is mapped to a respective one of the plurality of output ports (i.e., second communication regions) within the simulated environment. In one embodiment, the plurality of second communication regions includes four regions and the plurality of distinct wavelength channels includes four channels that are each mapped to a corresponding one of the four regions. In other embodiments, there may be a different number of the second communication regions (e.g., 8 regions) and a different number of channels (e.g., 8 channels) that are each mapped to a respective one of the second communication regions.
Block 912 illustrates performing an operational simulation of the physical device within the simulated environment operating in response to one or more excitation sources to determine performance loss values at a target wavelength and one or more delta wavelengths. More specifically, in some embodiments (and as illustrated in
Consequently, the operational simulation simulates an interaction between the photonic device (i.e., the photonic integrated circuit) and a physical stimuli (i.e., one or more excitation sources) to determine a simulated output of the photonic device (e.g., at one or more of the output ports or regions) in response to the physical stimuli. The interaction may correspond to any one of, or combination of a perturbation, retransmission, attenuation, dispersion, refraction, reflection, diffraction, absorption, scattering, amplification, or otherwise of the physical stimuli within electromagnetic domain due, at least in part, to the structural parameters of the photonic device and underlying physics governing operation of the photonic device. Thus, the operational simulation simulates how the field response of the simulated environment changes due to the excitation source over a plurality of time steps (e.g., from an initial to final time step with a pre-determined step size).
In some embodiments, the simulated output may be utilized to determine one or more performance metrics of the physical device. For example, the excitation source may correspond to a selected one of a plurality of distinct wavelength channels that are each mapped to one of the plurality of output ports. The excitation source may originate at or be disposed proximate to the first communication region (i.e., input port) when performing the operational simulation. During the operational simulation, the field response at the output port mapped to the selected one of the plurality of distinct wavelength channels may then be utilized to determine a simulated power transmission of the photonic integrated circuit for the selected distinct wavelength channel. In other words, the operational simulation may be utilized to determine the performance metric that includes determining a simulated power transmission of the excitation source from the first communication region, through the design region, and to a respective one of the plurality of second communication regions mapped to the selected one of the plurality of distinct wavelength channels.
In some embodiments, the excitation source may cover the spectrum of all of the plurality of output ports (e.g., the excitation source spans at least the targeted frequency ranges for the bandpass regions for each of the plurality of distinct wavelength channels as well as the corresponding transition band regions, and at least portions of the corresponding stopband regions) to determine a performance metric (i.e., simulated power transmission) associated with each of the distinct wavelength channels for the photonic integrated circuit. In some embodiments, one or more frequencies that span the passband of a given one of the plurality of distinct wavelength channels is selected randomly to optimize the design (e.g., batch gradient descent while having a full width of each passband including ripple in the passband that meets the target specifications). In the same or other embodiments, each of the plurality of distinct wavelength channels has a common bandwidth with different center wavelengths.
In some embodiments of the present disclosure and as illustrated in
The performance metric may then be used to generate a performance loss value for the set of perturbed structural parameters 806. The performance loss value may correspond to a difference between the performance metric and a target performance metric of the physical device. At block 914, a minimum performance loss value among the loss values calculated at the target wavelength and the delta wavelengths is determined and the minimum performance loss value is used as the performance loss value for the set of perturbed structural parameters 806 to be used for optimization.
The method 900 then proceeds to the for-loop end block 916. If further perturbed structural parameters 806 remain to be processed, then the method 900 returns to for-loop start block 906 to process the next set of perturbed structural parameters 806. Otherwise, if performance loss values have been obtained for all of the perturbed structural parameters 806, then the method advances to block 918.
At block 918, the performance loss values 822 are combined to generate a combined performance loss value. As discussed above, any suitable technique may be used to combine the separate performance loss values, including but not limited to linear combination and non-linear combination based on sensitivities for each operating condition.
Block 920 shows determining a loss metric based on the combined performance loss value and a fabrication loss associated with a minimum feature size. In some embodiments the loss metric is determined via a loss function that includes both the performance loss value and the fabrication loss as input values. In some embodiments, a minimum feature size for the design region of the simulated environment may be provided to promote fabricability of the design generated by the inverse design process. The fabrication loss is based, at least in part, on the minimum feature size and the perturbed structural parameters of the design region. More specifically, the fabrication loss enforces the minimum feature size for the design such that the design region does not have structural elements with a diameter less than the minimum feature size. This helps this system provide designs that meet certain fabricability and/or yield requirements. In some embodiments the fabrication loss also helps enforce binarization of the design (i.e., rather than mixing the first and second materials together to form a third material, the design includes regions of the first material and the second material that are inhomogeneously interspersed).
In some embodiments the fabrication loss is determined by generating a convolution kernel (e.g., circular, square, octagonal, or otherwise) with a width equal to the minimum feature size. The convolution kernel is then shifted through the design region of the simulated environment to determine voxel locations (i.e., individual voxels) within the design region that fit the convolution kernel within the design region without extending beyond the design region. The convolution kernel is then convolved at each of the voxel locations with the structural parameters associated with the voxel locations to determine first fabrication values. The structural parameters are then inverted and the convolution kernel is convolved again at each of the voxel locations with the inverted structural parameters to determine second fabrication values. The first and second fabrication values are subsequently combined to determine the fabrication loss for the design region. This process of determining the fabrication loss may promote structural elements of the design region having a radius of curvature less having a magnitude of less than a threshold size (i.e., inverse of half the minimum feature size).
Block 922 illustrates backpropagating the loss metric via the loss function through the simulated environment to determine an influence of changes in the structural parameters on the loss metric (i.e., structural gradient). The loss metric is treated as an adjoint or virtual source and is backpropagated incrementally from a final time step to earlier time steps in a backwards simulation to determine the structural gradient of the physical device.
Block 924 shows revising a design of the physical device (e.g., generated a revised description) by updating the structural parameters of the initial design 836 to adjust the loss metric. In some embodiments, adjusting for the loss metric may reduce the loss metric. However, in other embodiments, the loss metric may be adjusted or otherwise compensated in a manner that does not necessarily reduce the loss metric, In one embodiment, adjusting the loss metric may maintain fabricability while providing a general direction within the parameterization space to obtain designs that will ultimately result in increased performance while also maintaining device fabricability and targeted performance metrics. In some embodiments, the revised description is generated by utilizing an optimization scheme after a cycle of operational and adjoint simulations via a gradient descent algorithm, Markov Chain Monte Carlo algorithm, or other optimization techniques. Put in another way, iterative cycles of simulating the physical device, determining a loss metric, backpropagating the loss metric, and updating the structural parameters to adjust the loss metric may be successively performed until the loss metric substantially converges such that the difference between the performance metric and the target performance metric is within a threshold range while also accounting for fabricability and binarization due to the fabrication loss. By using multiple perturbed structural parameters to determine the performance loss value, the update of the initial design 836 will also account for robustness to differing operating conditions during fabrication. In some embodiments, the term “converges” may simply indicate the difference is within the threshold range and/or below some threshold value.
At decision block 926, a determination is made regarding whether the loss metric substantially converges such that the difference between the performance metric and the target performance metric is within a threshold range. Iterative cycles of simulating the physical device with the excitation source selected from the plurality of distinct wavelength channels, backpropagating the loss metric, and revising the design by updating the structural parameters to reduce the loss metric until the loss metric substantially converges such that the difference between the performance metric and the target performance metric is within a threshold range. In some embodiments, the structural parameters of the design region of the integrated photonic circuit are revised when performing the cycles to cause the design region of the photonic integrated circuit to optically separate each of the plurality of distinct wavelength channels from a multi-channel optical signal received via the first communication region and guide each of the plurality of distinct wavelength channels to the corresponding one of the plurality of second communication regions.
If the determination is that the loss metric has not converged, then the result of decision block 926 is NO, and the method 900 returns to block 904 to iterate on the revised initial design 836. Otherwise, if the determination is that the loss metric has converged, then the result of decision block 926 is YES and the method 900 advances to block 928.
Block 928 illustrates outputting an optimized design of the physical device in which the structural parameters have been updated to have the difference between the performance metric and the target performance metric within a threshold range while also enforcing a minimum feature size and binarization. The method 900 then proceeds to an end block and terminates.
As can be seen in the chart, the performance using both the naïve process and the process described in
The output sensor device 1106 may include any suitable type of device for measuring the output of the photonic device 1102, including but not limited to one or more photodiodes or other light sensors configured to measure the intensity and/or wavelength of the output. The temperature controller 1108 may be any type of logic, processor, or other type of computing device configured to control one or more temperature management devices 1104 based on measurements performed by the output sensor device 1106. In some embodiments, one or more temperature management devices 1104 may be used, and any suitable type of temperature management devices 1104, including but not limited to heaters (for increasing an operating temperature); and fans, coolers, or vents (for decreasing an operating temperature), may be used.
The output sensor device 1106, upon measuring the intensity and/or wavelength of the output, provides the measurement to a temperature controller 1108. The temperature controller 1108 may compare the measurement to a target measurement, and may use the temperature management devices 1104 to change the operating temperature of the photonic device 1102, thereby shifting the performance profile of the photonic device 1102 and bringing the measurement closer to the target measurement. In some embodiments, a feedback control loop including but not limited to a proportional-integral-derivative (PID) controller may be implemented by the temperature controller 1108, wherein the target measurement is the setpoint, the controller output is settings for one or more of the temperature management devices 1104, and the process value is the performance measured by the output sensor device 1106.
In the preceding description, numerous specific details are set forth to provide a thorough understanding of various embodiments of the present disclosure. One skilled in the relevant art will recognize, however, that the techniques described herein can be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring certain aspects.
Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
The order in which some or all of the blocks appear in each method flowchart should not be deemed limiting. Rather, one of ordinary skill in the art having the benefit of the present disclosure will understand that actions associated with some of the blocks may be executed in a variety of orders not illustrated, or even in parallel.
The processes explained above are described in terms of computer software and hardware. The techniques described may constitute machine-executable instructions embodied within a tangible or non-transitory machine (e.g., computer) readable storage medium, that when executed by a machine will cause the machine to perform the operations described. Additionally, the processes may be embodied within hardware, such as an application specific integrated circuit (“ASIC”) or otherwise.
The above description of illustrated embodiments of the invention, including what is described in the Abstract, is not intended to be exhaustive or to limit the invention to the precise forms disclosed. While specific embodiments of, and examples for, the invention are described herein for illustrative purposes, various modifications are possible within the scope of the invention, as those skilled in the relevant art will recognize.
These modifications can be made to the invention in light of the above detailed description. The terms used in the following claims should not be construed to limit the invention to the specific embodiments disclosed in the specification. Rather, the scope of the invention is to be determined entirely by the following claims, which are to be construed in accordance with established doctrines of claim interpretation.
