IP Library Granted Patent US 12,619,677
Granted Patent B2
US 12,619,677 · App. 17/670,284 · Granted May 5, 2026

Binary optimization using shallow boson sampling

Inventors: Hugo Wallner (London, GB); Kamil Bradler (Toronto, CA)
Assignee: ORCA Computing Limited
G06F17/11G06N10/60
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Quick Facts
Patent No.
US 12,619,677
App. No.
17/670,284
Granted
May 5, 2026
Kind
B2
Abstract

The present disclosure describes a system with a boson sampler that generates an output bosonic state by performing a transformation on an input bosonic state and produces measurement outcomes indicating the presence or absence of bosons in output modes. A controller of the system receives these measurement outcomes, generates binary sequences based on the presence or absence of bosons, and determines a solution to a binary optimization problem.

Claims (49)

1 . A system comprising:

a photonic boson sampler comprising:

a set of one or more light sources configured to generate an input state comprising a plurality of input modes;

a reconfigurable shallow interferometer comprising one or more configurable parameters, the reconfigurable shallow interferometer configured to generate an output state comprising a plurality of output modes by performing a transformation on the input state, wherein the transformation is dependent on one or more parameter values of the one or more configurable parameters; and

an arrangement of one or more photon detectors configured to produce a measurement outcome indicative of a presence or absence of photons in the plurality of output modes of the output state; and

a controller configured to:

receive measurement outcomes from the photonic boson sampler, the measurement outcomes generated by the photonic boson sampler being operated multiple times;

generate binary sequences based on the measurement outcomes, wherein values of the binary sequences are based on the presence or absence of photons in output modes of output states generated by the photonic boson sampler; and

determine a solution to a binary optimization problem based at least in part on the generated binary sequences.

2 . The system of claim 1 , wherein to generate the binary sequences, the controller is configured to:

map a first measurement outcome to a first binary sequence, wherein each element of the first binary sequence corresponds to an output mode of a first output state and has a value based on whether one or more photons were present or absent in the output mode.

3 . The system of claim 1 , wherein:

the input state of the photonic boson sampler comprises M input modes, wherein M is an integer greater than or equal to two; and

the reconfigurable shallow interferometer comprises fewer than M(M−1)/2 multimodal operations.

4 . The system of claim 1 , wherein the plurality of input modes of the input state are a plurality of temporal modes.

5 . The system of claim 4 , wherein the reconfigurable shallow interferometer comprises one or more temporal mode coupling devices, wherein a temporal mode coupling device comprises a reconfigurable beam splitter and a delay line, the delay line configured to connect one input port of the reconfigurable beam splitter with one output port of the reconfigurable beam splitter.

6 . The system of claim 5 , wherein the reconfigurable beam splitter is capable of coupling modes with a reconfigurable reflection coefficient.

7 . The system of claim 5 , wherein the reconfigurable beam splitter comprises a Mach-Zehnder interferometer.

8 . The system of claim 4 , wherein the reconfigurable shallow interferometer comprises one or more temporal mode coupling devices, wherein a temporal mode coupling device comprises a quantum memory.

9 . The system of claim 1 , wherein the plurality of input modes of the input state are a plurality of spatial modes.

10 . The system of claim 9 , wherein the reconfigurable shallow interferometer comprises a spatial interferometer, the spatial interferometer comprising:

M input ports for inputting M input modes of the input state into the spatial interferometer;

M output ports for outputting M output modes of the output state from the spatial interferometer; and

a plurality of waveguides arranged to pass through the spatial interferometer to connect the M input ports to the M output ports;

wherein the plurality of waveguides are arranged to provide a plurality of coupling locations between pairs of the plurality of waveguides, wherein a reconfigurable beam splitter is arranged at each of the plurality of coupling locations such that at each coupling location of the plurality of coupling locations two modes of electromagnetic radiation carried by a pair of waveguides are capable of coupling with each other with a reconfigurable reflection coefficient.

11 . The system of claim 10 , wherein the plurality of coupling locations are arranged such that at least one of the M input modes couples with each of the other M−1 input modes in the spatial interferometer.

12 . The system of claim 10 , wherein the spatial interferometer comprises fewer than M(M−1)/2 coupling locations.

13 . The system of claim 10 , wherein the reconfigurable shallow interferometer is comprised in an integrated photonic circuit.

14 . The system of claim 1 , wherein:

the controller is configured to receive the measurement outcomes and generate the binary sequences until a stopping condition is satisfied; and

the controller is further configured to:

until the stopping condition is satisfied, update the one or more parameter values of the one or more configurable parameters based on an objective function characteristic of the binary optimization problem; and

when the stopping condition is satisfied, receive further measurement outcomes from the photonic boson sampler and generate further binary sequences based on the further measurement outcomes, wherein the controller is configured to determine the solution to the binary optimization problem based at least in part on the generated further binary sequences.

15 . A method for using a photonic boson sampler to determine a solution to a binary optimization problem, wherein the photonic boson sampler is operable to: prepare an input state comprising a plurality of input modes; generate an output state comprising output modes by performing a transformation on the input state using a reconfigurable shallow interferometer; and produce measurement outcomes indicative of a presence or absence of photons in the output modes of the output state, the method comprising:

receiving measurement outcomes from the photonic boson sampler, the measurement outcomes generated by the photonic boson sampler being operated multiple times;

generating binary sequences based on the measurement outcomes, wherein values of the binary sequences are based on the presence or absence of photons in output modes of output states generated by the photonic boson sampler, and

determining the solution to the binary optimization problem based at least in part on the generated binary sequences.

16 . The method of claim 15 , wherein determining the solution to the binary optimization problem comprises:

determining function values by evaluating an objective function using at least two of the generated binary sequences, the objective function characteristic of the binary optimization problem; and

identifying, based at least in part on a comparison of the function values, a binary sequence as the solution to the binary optimization problem.

17 . The method of claim 15 , wherein generating the binary sequences comprises:

mapping a first measurement outcome to a first binary sequence, wherein each element of the first binary sequence corresponds to an output mode of a first output state and has a value based on whether one or more photons were present or absent in the output mode.

18 . The method of claim 15 , wherein generating the binary sequences comprises:

mapping a first measurement outcome to a first binary sequence according to a first mapping under which each element of the first binary sequence corresponds to an output mode of a first output state and has a first value if one or more photons were present in the output mode of the first output state and a second value if no photons were present in the output mode of the first output state; and

mapping a second measurement outcome different than the first measurement outcome to a second binary sequence according to a second mapping under which each element of the second binary sequence corresponds to an output mode of a second output state and has the second value if one or more photons were present in the output mode of the second output state and the first value if no photons were present in the output mode of the second output state.

19 . A non-transitory computer-readable storage medium comprising stored instructions that, when executed by a computing device, cause the computing device to perform operations, wherein the computing device is communicatively coupled to a photonic boson sampler operable to: prepare an input state comprising a plurality of input modes; generate an output state comprising output modes by performing a transformation on the input state using a reconfigurable shallow interferometer; and produce measurement outcomes indicative of a presence or absence of photons in the output modes of the output state, the operations including:

receiving measurement outcomes from the photonic boson sampler, the measurement outcomes generated by the photonic boson sampler being operated multiple times;

generating binary sequences based on the measurement outcomes, wherein values of the binary sequences are based on the presence or absence of photons in output modes of output bosonic states generated by the photonic boson sampler; and

determining a solution to a binary optimization problem based at least in part on the generated binary sequences.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 15, 2022
From: WALLNER, HUGO; BRADLER, KAMIL
To: ORCA COMPUTING LIMITED
Reel/Frame 059014/0549 →
Priority Claims (2)
GB 2115490 · Oct 28, 2021 · national
GB 2116924 · Nov 24, 2021 · national
Continuity (1)
Related Publication 20230133597A1 · May 4, 2023
References Cited (22)
US 20150354938A1 · Mower et al. · 2015 [cited by applicant]
US 20210096384A1 · Bradler · 2021 [cited by examiner]
US 20210287773A1 · Lam et al. · 2021 [cited by applicant]
US 20220172092A1 · Roman · 2022 [cited by examiner]
WO WO2020232546A1 · 2020 [cited by applicant]
WO WO2022058757A1 · 2022 [cited by applicant]
WO WO2023012375A1 · 2023 [cited by applicant]
Brod et al., “Photonic implementation of boson sampling: a review”, in Advanced Photonics, vol. 1, Issue 3, 034001 (May 2019). https://doi.org/10.1117/1.AP.1.3.034001 (Year: 2019). [cited by examiner]
Arrazola et al., “Quantum approximate optimization with Gaussian boson sampling”, Physical Review A 98, 012322 (2018), DOI: 10.1103/PhysRevA.98.012322 (Year: 2018). [cited by examiner]
Tillman et al., “Experimental boson sampling”, arXiv:1212.2240v1 (Year: 2012). [cited by examiner]
Zhong et al., “Experimental Gaussian Boson sampling”, Science Bulletin vol. 64, Issue 8, Apr. 30, 2019, pp. 511-515, https://doi.org/10.1016/j.scib.2019.04.007 (Year: 2019). [cited by examiner]
Aaronson, S. et al., “The Computational Complexity of Linear Optics,” arXiv:1011.3245, Nov. 14, 2010, pp. 1-94. [cited by applicant]
Bradler, K. et al., “Certain properties and applications of shallow bosonic circuits,” arXiv:2112.09766, Dec. 17, 2021, pp. 1-34. [cited by applicant]
Gard, B.T. et al., “An introduction to boson-sampling,” arXiv:1406.6767, Jun. 26, 2014, pp. 1-13. [cited by applicant]
Reck, M. et al., “Experimental realization of any discrete unitary operator,” Physical Review Letters, vol. 73, Jul. 1994, pp. 58-61. [cited by applicant]
Banchi, L. et al. “Training Gaussian boson sampling distributions,” [cited by applicant]
Crespi, A. et al. “Integrated multimode interferometers with arbitrary designs for photonic boson sampling,” [cited by applicant]
Olson, J.P. et al. “Sampling arbitrary photon-added or photon-subtracted squeezed states is in the same complexity class as boson sampling,” [cited by applicant]
PCT International Search Report, PCT Application No. PCT/GB2022/052731, Jan. 23, 2023, 5 pages. [cited by applicant]
Su, D. et al. “Error mitigation on a near-term quantum photonic device,” [cited by applicant]
UK Intellectual Property Office, Examination Report and Written Opinion, UK Patent Application No. GB2116924.8, Mar. 28, 2024, 6 pages. [cited by applicant]
Wang, H. et al. “Boson sampling with 20 input photons and a 60-mode interferometer in a 10 [cited by applicant]