A new method for compiling quantum algorithms is proposed and tested for a three qubit system. The proposed method is to decompose a a unitary matrix U, into a product of simpler U j via a neural network. These U j can then be decomposed into product of known quantum gates. Key to the effectiveness of this approach is the restriction of the set of training data generated to paths which approximate minimal normal subRiemannian geodesics, as this removes unnecessary redundancy and ensures the products are unique. The two neural networks are shown to work effectively, each individually returning low loss values on validation data after relatively short training periods. The two networks are able to return coefficients that are sufficiently close to the true coefficient values to validate this method as an approach for generating quantum circuits. There is scope for more work in scaling this approach for larger quantum systems.

Follow-up for ongoing management and monitoring of patients is important in clinical practice and research. While common, telephone follow-up is resource intensive and, in our experience, yields low success rates. Electronic communication using mobile devices including smartphones and tablets can provide efficient alternatives — including SMS (text), online forms and mobile apps. To assess attitudes towards electronic follow-up, we surveyed 642 parents and carers at Perth Children’s Hospital, targeting demographics, device ownership and attitudes towards electronic follow-up. Mobile phone ownership was effectively universal. Almost all respondents were happy to communicate electronically with the hospital. Promisingly, 93.2% of respondents were happy to receive follow-up SMSs from the hospital and 80.3% were happy to reply to SMS questions. There was less enthusiasm regarding other modalities, with 59.9% happy to use a website and 69.0% happy to use a mobile app. The results support the introduction of electronic communication for follow-up in our paediatric population.

In this paper, we define the class of hourglass automata, which are timed automata with bounded clocks that can be made to progress backwards as well as forwards at a constant rate. We then introduce a new clock update for timed automata that allows hourglass automata to be expressed. This allows us to show that language emptiness remains decidable with this update when the number of clocks is two or less. This is done by showing that we can construct a finite untimed graph using clock regions from any timed automaton that use this new update.

Background: Monitoring children's recovery postoperatively is important for routine care, research, and quality improvement. Although telephone follow-up is common, it is also time-consuming and intrusive for families. Using SMS messaging to communicate with families regarding their child's recovery has the potential to address these concerns. While a previous survey at our institution indicated that parents were willing to communicate with the hospital by SMS, data on response rates for SMS-based postoperative data collection is limited, particularly in pediatric populations. Aims:We conducted a feasibility study with 50 completed pain profiles obtained from patients at Perth Children's Hospital to examine response rates. Methods:We collected and classified daily average pain (0-10 parent proxy score) on each day after tonsillectomy until pain-free for two consecutive days. Results:We enrolled 62 participants and recorded 50 (81%) completed pain profiles, with 711 (97.9%) of 726 requests for a pain score receiving a response. Two families (3%) opted out of the trial, and 10 (16%) were lost to follow-up. Responses received were classified automatically in 92% of cases. No negative feedback was received, with a median (range) satisfaction score of 5 on a 5-point Likert scale (1 = very unhappy, 5 = very happy).Conclusions: This methodology is likely to generalize well to other simple clinical questions and produce good response rates in further similar studies. We expect SMS messaging to permit expanded longitudinal data collection and broader investigation into patient recovery than previously feasible using telephone follow-up at our institution.