Multiscale contiguous block pixel entangler for image recognition on hybrid quantum-classical computing system

A hybrid quantum-classical computing system, comprising:

• a quantum processor comprising a plurality of trapped ions, each of the trapped ions having two hyperfine states defining a qubit;
• a system controller configured to control one or more lasers configured to emit a laser beam, which is provided to trapped ions in the quantum processor;
• and
• a classical computer configured to:
• receive an input image having a two dimensional array of pixels arranged in columns and rows;
• control the system controller to encode pixel data of the input image onto the quantum processor using a plurality of column qubits and a plurality of row qubits, wherein the plurality of column qubits represents pixels along the column direction and the plurality of row qubits represents pixels along the row direction;
• control the system controller to perform a set of a convolutional layer operation and a pooling layer operation,
• the convolutional layer operation comprising applying a contiguous block pixel entangler that entangles a column qubit of the plurality of column qubits and a row qubit of the plurality of row qubits, depending on a pattern of a feature to detect in the input image;
• and
• the pooling layer operation comprising applying a series of one-qubit operations to the plurality of column qubits and the plurality of row qubits;
• control the system controller to perform a measurement operation comprising measuring a state of an output qubit among the plurality of column qubits and the plurality of row qubits;
• and
• output qubit state information relating to the measured state of the output qubit, wherein the qubit state information includes information relating to whether or not the feature is contained in the input image.

A hybrid quantum-classical computing system comprising non-volatile memory having a number of instructions stored therein which, when executed by one or more processors, causes the hybrid quantum-classical computing system to perform operations comprising:

• performing a data load operation comprising:
• receiving, by a classical computer, an input image having a two dimensional array of pixels arranged in columns and rows;
• and
• encoding, by a system controller, pixel data of the input image onto a quantum processor using a plurality of column qubits and a plurality of row qubits, wherein the plurality of column qubits represents pixels along the column direction and the plurality of row qubits represents pixels along the row direction;
• performing a set of a convolutional layer operation and a pooling layer operation,
• the convolutional layer operation comprising applying, by the system controller, a contiguous block pixel entangler that entangles a column qubit of the plurality of column qubits and a row qubit of the plurality of row qubits, depending on a pattern of a feature to detect in the input image;
• and
• the pooling layer operation comprising applying, by the system controller, a series of one-qubit operations to the plurality of column qubits and the plurality of row qubits;
• performing a measurement operation comprising measuring, by the system controller, a state of an output qubit among the plurality of column qubits and the plurality of row qubits;
• and
• outputting, by the classical computer, qubit state information relating to the measured state of the output qubit, wherein the qubit state information includes information relating to whether or not the feature is contained in the input image.