Multi-qubit correction for quantum annealers.

We present multi-qubit correction (MQC) as a novel postprocessing method for quantum annealers that views the evolution in an open-system as a Gibbs sampler and reduces a set of excited states to a new synthetic state with lower energy value. After sampling from the ground state of a given (Ising) Hamiltonian, MQC compares pairs of excited states to recognize virtual tunnels-i.e., a group of qubits that changing their states simultaneously can result in a new state with lower energy value-and successively converges to the ground state. Experimental results using D-Wave 2000Q quantum annealers demonstrate that MQC finds samples with notably lower energy values and improves the reproducibility of results when compared to recent hardware/software advances in the realm of quantum annealing, such as spin-reversal transforms, classical postprocessing techniques, and increased inter-sample delay between successive measurements.

Understanding Cybersecurity Threat Trends Through Dynamic Topic Modeling.

Cybersecurity threats continue to increase and are impacting almost all aspects of modern life. Being aware of how vulnerabilities and their exploits are changing gives helpful insights into combating new threats. Applying dynamic topic modeling to a time-stamped cybersecurity document collection shows how the significance and details of concepts found in them are evolving. We correlate two different temporal corpora, one with reports about specific exploits and the other with research-oriented papers on cybersecurity vulnerabilities and threats. We represent the documents, concepts, and dynamic topic modeling data in a semantic knowledge graph to support integration, inference, and discovery. A critical insight into discovering knowledge through topic modeling is seeding the knowledge graph with domain concepts to guide the modeling process. We use Wikipedia concepts to provide a basis for performing concept phrase extraction and show how using those phrases improves the quality of the topic models. Researchers can query the resulting knowledge graph to reveal important relations and trends. This work is novel because it uses topics as a bridge to relate documents across corpora over time.

Reinforcement Quantum Annealing: A Hybrid Quantum Learning Automata.

We introduce the notion of reinforcement quantum annealing (RQA) scheme in which an intelligent agent searches in the space of Hamiltonians and interacts with a quantum annealer that plays the stochastic environment role of learning automata. At each iteration of RQA, after analyzing results (samples) from the previous iteration, the agent adjusts the penalty of unsatisfied constraints and re-casts the given problem to a new Ising Hamiltonian. As a proof-of-concept, we propose a novel approach for casting the problem of Boolean satisfiability (SAT) to Ising Hamiltonians and show how to apply the RQA for increasing the probability of finding the global optimum. Our experimental results on two different benchmark SAT problems (namely factoring pseudo-prime numbers and random SAT with phase transitions), using a D-Wave 2000Q quantum processor, demonstrated that RQA finds notably better solutions with fewer samples, compared to the best-known techniques in the realm of quantum annealing.

Security policies and trust in ubiquitous computing.

Ubiquitous environments comprise resource-constrained mobile and wearable devices and computational elements embedded in everyday artefacts. These are connected to each other using both infrastructure-based as well as short-range ad hoc networks. Limited Internet connectivity limits the use of conventional security mechanisms such as public key infrastructures and other forms of server-centric authentication. Under these circumstances, peer-to-peer interactions are well suited for not just information interchange, but also managing security and privacy. However, practical solutions for protecting mobile devices, preserving privacy, evaluating trust and determining the reliability and accuracy of peer-provided data in such interactions are still in their infancy. Our research is directed towards providing stronger assurances of the reliability and trustworthiness of information and services, and the use of declarative policy-driven approaches to handle the open and dynamic nature of such systems. This paper provides an overview of some of the challenges and issues, and points out directions for progress.