# US 2026/0074801 A1 · Photon number determination using reframed trace data points > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2026/0074801 A1 - Document ID: US20260074801A1 - Status: Published application - Kind: A1 - Application number: 19/322,003 - Filed: 2025-09-08 - Published: 2026-03-12 - Earliest claimed: 2024-09-12 - Assignees: Xanadu Quantum Technologies Inc. - Applicants: Xanadu Quantum Technologies Inc. - Inventors: Zeyue NIU - Web page: https://patentgrep.com/patent/US20260074801A1 ## CPC - H04B 10/70: Photonic quantum communication - G06N 10/40: Physical realisations or architectures of quantum processors or components for manipulating qubits, e.g. qubit coupling or qubit control - G06N 20/00: Machine learning - H04B: TRANSMISSION - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract Systems, methods, and computer program products for determining a photon number. Electrical signal trace data is received by a signal processor. A plurality of trace data points are defined based on the received electrical signal trace data. Each trace data point includes both a signal value and a time value indicating the position of that trace data point within the electrical signal trace. The trace data points are input to a machine learning model trained to output predicted photon number data usable to determine the photon number corresponding to the received electrical signal trace. The machine learning model can be trained to output predicted photon number data based on an incomplete set of trace data points, and even individual trace data points. This can allow the photon number to be predicted when data is partially missing or lost, and/or before the entire electrical signal trace has been received. ## Claims ### Claim 1 A method comprising: receiving, by a signal processor, electrical signal trace data from a photon-number resolving detector; determining, by the signal processor, a predicted photon number associated with the electrical signal trace data by inputting a plurality of trace data points to a machine learning model trained to output predicted photon number data in response to receiving one or more trace data points as input, wherein the plurality of trace data points are defined based on the received electrical signal trace data, and wherein each trace data point is defined to include a trace signal value and a trace data point time value; and transmitting, by the signal processor, an output signal based on the determined photon number. ### Claim 2 (depends on 1) The method of claim 1, wherein the signal processor is configured to define the output signal in response to determining that the predicted photon number has an associated prediction confidence level above a predefined confidence threshold. ### Claim 3 (depends on 1) The method of claim 1, wherein: the machine learning model is trained to output at least one point-specific predicted photon number value in response to each trace data point; and the predicted photon number is determined based on a plurality of point-specific predicted photon number values corresponding to the plurality of trace data points. ### Claim 4 (depends on 3) The method of claim 3, wherein: for at least one trace data point, the at least one point-specific predicted photon number value includes a plurality of photon number prediction sets; each photon number prediction set corresponds to a potential photon number and includes an associated photon number probability for that potential photon number; and the predicted photon number is determined as the potential photon number having the highest aggregate probability value across the plurality of trace data points. ### Claim 5 (depends on 1) The method of claim 1, wherein the machine learning model is defined as an autoregressive model to accommodate overlapping electrical signal trace data corresponding to a sequence of optical pulses received by the photon-number resolving detector. ### Claim 6 (depends on 1) The method of claim 1, further comprising receiving a first optical pulse at a photon-number resolving detector and transmitting the electrical signal trace data from the photon-number resolving detector to the signal processor, wherein the electrical signal trace data is produced by the photon-number resolving detector in response to the first optical pulse. ### Claim 7 (depends on 1) The method of claim 1, wherein: the output signal is a control signal that corresponds to the determined photon number; and the control signal is transmitted, by the signal processor, to a related signal switch, wherein the control signal is defined to cause the related signal switch to switch to a specified routing path to route a related optical pulse in response to the control signal. ### Claim 8 A computer program product comprising a non-transitory computer readable medium having computer executable instructions stored thereon, the instructions for configuring one or more processors to perform a method comprising: receiving electrical signal trace data from a photon-number resolving detector; determining a predicted photon number associated with the electrical signal trace data by inputting a plurality of trace data points to a machine learning model trained to output predicted photon number data in response to receiving one or more trace data points as input, wherein the plurality of trace data points are defined based on the received electrical signal trace data, and wherein each trace data point is defined to include a trace signal value and a trace data point time value; and transmitting an output signal based on the determined photon number. ### Claim 9 (depends on 8) The computer program product of claim 8, wherein the instructions are defined to configure the one or more processors to define the output signal in response to determining that the predicted photon number has an associated prediction confidence level above a predefined confidence threshold. ### Claim 10 (depends on 8) The computer program product of claim 8, wherein: the machine learning model is trained to output at least one point-specific predicted photon number value in response to each trace data point; and the instructions are defined to configure the one or more processors to determine the predicted photon number based on a plurality of point-specific predicted photon number values corresponding to the plurality of trace data points. ### Claim 11 (depends on 10) The computer program product of claim 10, wherein: for at least one trace data point, the at least one point-specific predicted photon number value includes a plurality of photon number prediction sets; each photon number prediction set corresponds to a potential photon number and includes an associated photon number probability for that potential photon number; and the instructions are defined to configure the one or more processors to determine the predicted photon number as the potential photon number having the highest aggregate probability value across the plurality of trace data points. ### Claim 12 (depends on 8) The computer program product of claim 8, wherein the machine learning model is defined as an autoregressive model to accommodate overlapping electrical signal trace data corresponding to a sequence of optical pulses received by the photon-number resolving detector. ### Claim 13 (depends on 8) The computer program product of claim 8, wherein the instructions are defined to configure the one or more processors to: define the output signal as a control signal that corresponds to the determined photon number; and transmit the control signal to a related signal switch, wherein the control signal is defined to cause the related signal switch to switch to a specified routing path to route a related optical pulse in response to the control signal. ### Claim 14 A system comprising: one or more processors; and one or more non-transitory storage mediums having stored thereon a machine learning model trained to output predicted photon number data in response to receiving one or more trace data points as input; wherein the one or more processors are configured to: receive electrical signal trace data from a photon-number resolving detector; determine a predicted photon number associated with the electrical signal trace data by inputting a plurality of trace data points to the machine learning model, wherein the plurality of trace data points are defined based on the received electrical signal trace data, and wherein each trace data point is defined to include a trace signal value and a trace data point time value; and transmit an output signal based on the determined photon number. ### Claim 15 (depends on 14) The system of claim 14, wherein the one or more processors is further configured to define the output signal in response to determining that the predicted photon number has an associated prediction confidence level above a predefined confidence threshold. ### Claim 16 (depends on 14) The system of claim 14, wherein: the machine learning model is trained to output at least one point-specific predicted photon number value in response to each trace data point; and the one or more processors is configured to determine the predicted photon number based on a plurality of point-specific predicted photon number values corresponding to the plurality of trace data points. ### Claim 17 (depends on 16) The system of claim 16, wherein: for at least one trace data point, the at least one point-specific predicted photon number value includes a plurality of photon number prediction sets; each photon number prediction set corresponds to a potential photon number and includes an associated photon number probability for that potential photon number; and the one or more processors is configured to determine the predicted photon number as the potential photon number having the highest aggregate probability value across the plurality of trace data points. ### Claim 18 (depends on 14) The system of claim 14, wherein the machine learning model is defined as an autoregressive model to accommodate overlapping electrical signal trace data corresponding to a sequence of optical pulses received by the photon-number resolving detector. ### Claim 19 (depends on 14) The system of claim 14, further comprising a photon-number resolving detector, wherein the photon-number resolving detector is operable to: receive a first optical pulse; produce the electrical signal trace data in response to the first optical pulse; and transmit the electrical signal trace data to the one or more processors. ### Claim 20 (depends on 14) The system of claim 14, wherein the one or more processors is configured to: define the output signal as a control signal that corresponds to the determined photon number; and transmit the control signal to a related signal switch, wherein the control signal is defined to cause the related signal switch to switch to a specified routing path to route a related optical pulse in response to the control signal.