There is described herein a quantum computing system, quantum processor, and method of operating a quantum computing system. The quantum computing system comprises a quantum control system configured for at least one of delivery and receipt of multiplexed optical signals. At least one optical fiber is coupled to the quantum control system for carrying the multiplexed optical signals, and a quantum processor is disposed inside a cryogenics apparatus and coupled to the at least one optical fiber. The quantum processor comprises: at least one converter configured for converting between the multiplexed optical signals and microwave signals at different frequencies; and a plurality of solid-state quantum circuit elements coupled to the at least one converter and addressable by respective ones of the microwave signals at different frequencies.

A method includes obtaining a plurality of entangled qubits, with high fault tolerance, represented by a lattice structure. The lattice structure includes a plurality of contiguous lattice cells. A first subset of the plurality of entangled qubits defines a first plane, and a second subset of the plurality of entangled qubits defines a second plane that is parallel to and offset from the first plane. The plurality of entangled qubits includes a defect qubit that is entangled with at least one face qubit on the first plane and at least one edge qubit on the second plane.

Embodiments described herein provide systems and methods for computing matrix-vector multiplication operations. The systems and methods generally compute the matrix-vector multiplication operations using analog optical signals. The systems and methods allow completely reconfigurable multiplication operations and may be used as application specific computational hardware for deep neural networks.

Making failure scenarios using adversarial reinforcement learning is performed by storing, in a first storage, a variety of first experiences of failures of a player agent due to an adversarial agent, and performing a simulation of an environment including the player agent and the adversarial agent. It also includes calculating a similarity of a second experience of a failure of the player agent in the simulation and each of the variety of first experiences in the first storage, and updating the first storage by adding the second experience as a new first experience of the variety of first experiences in response to the similarity being less than a threshold. Additionally, the use of adversarial reinforcement learning can include training the adversarial agent by using at least one of the plurality of first experiences in the first storage to generate an adversarial agent having diverse experiences.

The present disclosure pertains to autonomous control of an imaging system. In some embodiments, training information including at least a plurality of images and action information are received. The plurality of images and action information are provided to a prediction model to train the prediction model. Further, an image capturing device is controlled to capture an image of a portion of a living organism, the image is processed, via the prediction model, to determine an action to be taken with respect to the image, and the determined action is taken with respect to the image.

Systems and methods that include: providing input information in an electronic format; converting at least a part of the electronic input information into an optical input vector; optically transforming the optical input vector into an optical output vector based on an optical matrix multiplication; converting the optical output vector into an electronic format; and electronically applying a non-linear transformation to the electronically converted optical output vector to provide output information in an electronic format. In some examples, a set of multiple input values are encoded on respective optical signals carried by optical waveguides. For each of at least two subsets of one or more optical signals, a corresponding set of one or more copying modules splits the subset of one or more optical signals into two or more copies of the optical signals. For each of at least two copies of a first subset of one or more optical signals, a corresponding multiplication module multiplies the one or more optical signals of the first subset by one or more matrix element values using optical amplitude modulation. For results of two or more of the multiplication modules, a summation module produces an electrical signal that represents a sum of the results of the two or more of the multiplication modules.

Systems and methods performed for generating authentication information for an image using optical computing are provided. When a user takes a photo of an object, an optical authentication system receives light reflected and/or emitted from the object. The system also receives a random key from an authentication server. The system converts the received light to plenoptic data and uploads it to the authentication server. In addition, the system generates an optical hash of the received light using the random key, converts the generated optical hash to a digital optical hash, and uploads the digital optical hash to the authentication server. When the authentication server receives the upload, it verifies whether the time of the upload is within a certain threshold time from the sending of the random key and whether the digital optical hash was generated from the same light as the plenoptic data.

Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously enable anomaly detection resulting from construction—or other activity based on image processing that may advantageously detect/notify/prevent damage to a fiber optic network infrastructure before such damage occurs.

Photonic processors are described. The photonic processors described herein are configured to perform matrix multiplications (e.g., matrix vector multiplications). Matrix multiplications are broken down in scalar multiplications and scalar additions. Some embodiments relate to devices for performing scalar additions in the optical domain. One optical adder, for example, includes an interferometer having a plurality of phase shifters and a coherent detector. Leveraging the high-speed characteristics of these optical adders, some processors are sufficiently fast to support clocks in the tens of gigahertz of frequency, which represent a significant improvement over conventional electronic processors.

Systems and methods for the optical control of qubits and other quantum particles with spatial light modulators (SLM) for quantum computing and quantum simulation are disclosed herein. The system may include a particle system configured to provide an ordered array comprising a multiplicity of quantum particles or a multiplicity of qubits, an optical source, a SLM configured to project a structured illumination pattern capable of individually addressing one or more quantum particles or qubits of the ordered array, and a SLM controller.