Image reconstruction from photon sparse data

We report an algorithm for reconstructing images when the average number of photons recorded per pixel is of order unity, i.e. photon-sparse data. The image optimisation algorithm minimises a cost function incorporating both a Poissonian log-likelihood term based on the deviation of the reconstructed image from the measured data and a regularization-term based upon the sum of the moduli of the second spatial derivatives of the reconstructed image pixel intensities. The balance between these two terms is set by a bootstrapping technique where the target value of the log-likelihood term is deduced from a smoothed version of the original data. When compared to the original data, the processed images exhibit lower residuals with respect to the true object. We use photon-sparse data from two different experimental systems, one system based on a single-photon, avalanche photo-diode array and the other system on a time-gated, intensified camera. However, this same processing technique could most likely be applied to any low photon-number image irrespective of how the data is collected

The spatial state of non-interacting photons

High-dimensional quantum systems are becoming an increasingly important area of study. Due to their ability to encode more information than a two-dimensional system, high-dimensional systems are useful in many applications, from quantum communication to quantum computing. In particular, spatial states of light, such as orbital angular momentum and spatial position, are inherently high-dimensional by nature and lend themselves well to manipulation and measurement. As light is commonly used in communication applications, spatial states could extend the information capacity of quantum communication and make it easier to detect eavesdroppers in the system. This thesis comprises four experiments in which the spatial state of photons is manipulated and measured. The first experiment describes a filter for two dimensional anti-symmetric spatial states. We use a pair of photons entangled in multiple orbital angular momentum states in order to test the filter. We are able to manipulate which two-dimensional subspaces are in symmetric states and which are in anti-symmetric states, and as such we are able to filter out particular subspaces, effectively engineering high-dimensional states via Hong-Ou-Mandel interference. In the second experiment, we use the anti-symmetric state filter in a four-photon system. We begin with two pairs of photons, with entanglement within the pairs but not between the pairs. Combining one photon from each pair in our anti-symmetric state filter, we create entanglement between the other two photons, achieving entanglement swapping. Additionally, due to the two-dimensional nature of the filter, we transcribe entanglement into several two-dimensional subspaces in the process. In the third experiment, we investigate the quantum teleportation that occurs as a side effect of the entanglement swapping. We demonstrate teleportation of several two-dimensional OAM states, and we describe the result of attempted high dimensional teleportation. In the fourth and final experiment, we turn our attention from the OAM of light to the spatial position of light. Using our four-photon system and anti-symmetric state filter, we demonstrate ghost imaging between photons that have never interacted. This is enabled by taking advantage of the correlations produced when entanglement swapping occurs in the filter

Discriminating single-photon states unambiguously in high dimensions

The ability to uniquely identify a quantum state is integral to quantum science, but for non-orthogonal states, quantum mechanics precludes deterministic, error-free discrimination. However, using the non-deterministic protocol of unambiguous state discrimination (USD) enables error-free differentiation of states, at the cost of a lower frequency of success. We discriminate experimentally between non-orthogonal, high-dimensional states encoded in single photons; our results range from dimension $d=2$ to $d=14$. We quantify the performance of our method by comparing the total measured error rate to the theoretical rate predicted by minimum-error state discrimination. For the chosen states, we find a lower error rate by more than one standard deviation for dimensions up to $d=12$. This method will find immediate application in high-dimensional implementations of quantum information protocols, such as quantum cryptography.Comment: 4 pages + 3 pages supplementary, 4 figure

The impact of symptom clusters on endocrine therapy adherence in patients with breast cancer

Background: When taken as prescribed, endocrine therapy is effective in reducing risk of recurrence and mortality in the treatment of patients with breast cancer. However, treatment side effects can act as a barrier to medication adherence. Existing research has not identified any specific side effects as consistent predictors of nonadherence. Our aim was to explore the influence of symptom clusters on self-reported adherence in patients with breast cancer. Methods: A cross-sectional online survey was conducted, including patients with breast cancer currently or previously prescribed endocrine therapy (N=1051). This included measures of self-reported endocrine therapy adherence and common symptoms among this population (insomnia, depression, anxiety, fatigue, musculoskeletal, and vasomotor symptoms). Results: Unintentional nonadherence was higher than intentional nonadherence (50.8% vs 31.01%). The most troublesome symptom was insomnia (73.83% displayed probable insomnia disorder). K-means cluster analysis identified 2 symptom clusters: overall High symptoms, and overall Low symptoms. Participants in the Low symptoms cluster were significantly more likely to be classed as adherent based on unintentional and intentional items. Conclusions: Nonadherence was high in the current sample, and significantly more likely in participants reporting overall severe symptoms. Clinicians should be aware of the scale of common side effects and facilitate open conversation about potential barriers to adherence. Follow-up care should include assessment of common symptoms and signpost patients to appropriate support or treatment when required. Future research should explore potential for a central symptom to act as a target for intervention, to relieve overall side effect burden and facilitate better medication adherence

The impact of symptom clusters on endocrine therapy adherence in patients with breast cancer

Background: When taken as prescribed, endocrine therapy is effective in reducing risk of recurrence and mortality in the treatment of patients with breast cancer. However, treatment side effects can act as a barrier to medication adherence. Existing research has not identified any specific side effects as consistent predictors of nonadherence. Our aim was to explore the influence of symptom clusters on self-reported adherence in patients with breast cancer. Methods: A cross-sectional online survey was conducted, including patients with breast cancer currently or previously prescribed endocrine therapy (N=1051). This included measures of self-reported endocrine therapy adherence and common symptoms among this population (insomnia, depression, anxiety, fatigue, musculoskeletal, and vasomotor symptoms). Results: Unintentional nonadherence was higher than intentional nonadherence (50.8% vs 31.01%). The most troublesome symptom was insomnia (73.83% displayed probable insomnia disorder). K-means cluster analysis identified 2 symptom clusters: overall High symptoms, and overall Low symptoms. Participants in the Low symptoms cluster were significantly more likely to be classed as adherent based on unintentional and intentional items. Conclusions: Nonadherence was high in the current sample, and significantly more likely in participants reporting overall severe symptoms. Clinicians should be aware of the scale of common side effects and facilitate open conversation about potential barriers to adherence. Follow-up care should include assessment of common symptoms and signpost patients to appropriate support or treatment when required. Future research should explore potential for a central symptom to act as a target for intervention, to relieve overall side effect burden and facilitate better medication adherence

The impact of medication side effects on adherence and persistence to hormone therapy in breast cancer survivors: A qualitative systematic review and thematic synthesis

BackgroundHormone Therapy (HT) reduces the risk of breast cancer recurrence and mortality in women with breast cancer. Despite these clinical benefits, rates of HT non-adherence and non-persistence are high. Research suggests this may be due to the impact of HT side effects. However, little research has explored the individual contribution of side effects to non-adherence and non-persistence behaviours, thereby hindering the implementation of targeted intervention strategies. Our aim is to review the published literature on breast cancer survivors’ lived experiences of HT side effects and explore how these may be related to non-adherence and non-persistence behaviour.MethodsElectronic searches were conducted from inception to May 2020, utilising Cochrane CENTRAL, Medline, Embase, Web of Science and PsycINFO databases. Searches included a combination of terms related to breast cancer, adherence, hormone therapy and side effects.ResultsSixteen eligible papers were identified, and study quality was high. Data were thematically synthesised into four analytical themes, which encompassed 13 descriptive sub-themes: ‘Daily impact of side-effects’, ‘Role of Health Care Professionals’, ‘Managing HT side-effects’, and ‘Weighing up the pros and cons’.ConclusionsHT side effects significantly impact breast cancer survivor's quality of life. A lack of support from healthcare providers leads to self-management strategies, which negatively affects adherence and persistence behaviour