Abstract: A method of processing network security alerts includes receiving a plurality of security alerts generated by network security devices in a network, each security alert comprising alert data relating to the security alert and specifying an alert time and a network device, a user identity associated with the security alert, or both. A group of related alerts are selected from the plurality of security alerts, the group of related alerts having an alert time within a given time window and associated with one or both of: a given network device; and a given user identity. Alert data for the selected alerts is provided as an input data set for a machine learning model configured to generate an anomaly score. An action is then performed in dependence on the anomaly score.

Abstract: The present invention provides an improved method and system for variational quantum algorithms (VQA). Procedures set out herein include receiving a quantum circuit for implementing the VQA, the quantum circuit being parameterised by a set of quantum circuit parameters. A cost function for the circuit is formulated as a non-convex polynomial optimisation problem. Next moment/Sums of Squares, SOS, relaxations are applied to the non-convex polynomial optimisation problem to generate a hierarchy of semidefinite programming (SDP) relaxations that approximate the non-convex polynomial optimisation problem. These SDP relaxations are then solved using classical optimisation algorithms. The solutions are used to update the quantum circuit parameters, thereby providing an improved VQA circuit. Upon repeated iterations of the procedure, this provably converges toward the optimal VQA circuit for the problem at hand.

Abstract: The disclosed system and method automate the transpilation of query source code to a distributed data processing system. The process involves instantiating transpiler libraries and source code, executing the source code, and transpiling the source code into a transpiled code using the transpiler libraries. A machine learning algorithm is utilized to control the operation of the transpilation process wherever different transpilation options are available as an automated mechanism for adapting transpilation based on tracked downstream operational characteristics. The system is configured for automatic source code generation in the target language as an output, which can then be deployed to a distributed data processing or query system. Variants are described using a combination of test and production environments for initial testing and tuning of the machine learning model architecture until a performance threshold is met. A same code segment may be transpiled periodically for continual automatic optimization.

Abstract: A method of compressing a quantum circuit using a quantum circuit compressor is disclosed. The method comprises receiving data defining a quantum circuit and identifying a section of the quantum circuit that matches a predetermined circuit template. The circuit template specifies a first arrangement of quantum gates including at least one SWAP gate for implementing a non-local interaction and is associated with a predetermined second arrangement of quantum gates that does not include the SWAP gate. The compressor determines whether the circuit section meets a compression criterion. In response to determining that the circuit section meets the compression criterion; the compressor modifies the circuit definition to replace the first arrangement of quantum gates with the second arrangement of quantum gates, and outputs the modified circuit definition, for example to a quantum computing system for execution of the modified circuit.