Information criteria for efficient quantum state estimation

Recently several more efficient versions of quantum state tomography have been proposed, with the purpose of making tomography feasible even for many-qubit states. The number of state parameters to be estimated is reduced by tentatively introducing certain simplifying assumptions on the form of the quantum state, and subsequently using the data to rigorously verify these assumptions. The simplifying assumptions considered so far were (i) the state can be well approximated to be of low rank, or (ii) the state can be well approximated as a matrix product state. We add one more method in that same spirit: we allow in principle any model for the state, using any (small) number of parameters (which can, e.g., be chosen to have a clear physical meaning), and the data are used to verify the model. The proof that this method is valid cannot be as strict as in above-mentioned cases, but is based on well-established statistical methods that go under the name of "information criteria." We exploit here, in particular, the Akaike Information Criterion (AIC). We illustrate the method by simulating experiments on (noisy) Dicke states

Consistency of the Shannon entropy in quantum experiments

The consistency of the Shannon entropy, when applied to outcomes of quantum experiments, is analysed. It is shown that the Shannon entropy is fully consistent and its properties are never violated in quantum settings, but attention must be paid to logical and experimental contexts. This last remark is shown to apply regardless of the quantum or classical nature of the experiments.Comment: 12 pages, LaTeX2e/REVTeX4. V5: slightly different than the published versio

Reference priors for high energy physics

Bayesian inferences in high energy physics often use uniform prior distributions for parameters about which little or no information is available before data are collected. The resulting posterior distributions are therefore sensitive to the choice of parametrization for the problem and may even be improper if this choice is not carefully considered. Here we describe an extensively tested methodology, known as reference analysis, which allows one to construct parametrization-invariant priors that embody the notion of minimal informativeness in a mathematically well-defined sense. We apply this methodology to general cross section measurements and show that it yields sensible results. A recent measurement of the single top quark cross section illustrates the relevant techniques in a realistic situation

Development of criteria und procedures for the evaluation of the European Action Plan of Organic Food and Farming

Within the EU funded project ORGAP a toolbox for the evaluation of the European as well as national action plans for organic food and farming has been developed (www.orgap.org). This toolbox was based on a comparative analysis of national action plans in eight countries (CH, UK, DE, IT, DK, SI, CZ, NL, ES), a meta-evaluation of existing evaluations of national action plans, workshops with national stakeholders and a European Advisory Committee, interviews with experts. Furthermore synergies and conflicts between national and the European Action Plan were identified

Lessons learnt from ORGAP Project – planning, implementation and evaluation of Action Plans for Organic Food and Farming

Within the EU funded project ORGAP, a toolbox was developed for the evaluation of the European as well as national action plans for organic food and farming. Also recommendations and a resource manual for policy makers and stakeholders were developed. These were based on the analysis of national Organic Action Plans as well as stakeholder and expert consultation. The analysis showed that several EU member states have emphasised the need to balance supply-push policies with more market-focused demand-pull policies. An integrated approach is required and this has been to differing degrees through the formulation of multi-functional Organic Action Plans (OAPs), which also adress the dual roles of organic farming (from a policy perspective) to provide public goods and satisfy consumer demand. Eight Organic Action Plans, reviewed in the ORGAP project, vary with regard to the elaboration process, targets, objectives and the emphasis of measures on certain areas (e.g. market versus environment orientation). This variation is due to quite different political and socio-economic framework conditions for organic farming in these countries. It revealed that the weaknesses identified in the status quo analysis of the organic sector have only partly been translated to the targets and measures included in the action plan documents. Definition of the priorities for development of organic agriculture must be agreed by all relevant stakeholders. The priorities, and hence the programmes, will depend on correct analysis of the issues (and conflicts) that need to be addressed and clear objectives with measurable outcomes (for effective evaluation). For more information on the project, on the practical project manual and the evaluation toolbox for Organic Action Plans see project website www.orgap.or

Bayesian Analysis and Constraints on Kinematic Models from Union SNIa

The kinematic expansion history of the universe is investigated by using the 307 supernovae type Ia from the Union Compilation set. Three simple model parameterizations for the deceleration parameter (constant, linear and abrupt transition) and two different models that are explicitly parametrized by the cosmic jerk parameter (constant and variable) are considered. Likelihood and Bayesian analyses are employed to find best fit parameters and compare models among themselves and with the flat $\Lambda$CDM model. Analytical expressions and estimates for the deceleration and cosmic jerk parameters today ($q_0$ and $j_0$) and for the transition redshift ($z_t$) between a past phase of cosmic deceleration to a current phase of acceleration are given. All models characterize an accelerated expansion for the universe today and largely indicate that it was decelerating in the past, having a transition redshift around 0.5. The cosmic jerk is not strongly constrained by the present supernovae data. For the most realistic kinematic models the $1\sigma$ confidence limits imply the following ranges of values: $q_0\in[-0.96,-0.46]$, $j_0\in[-3.2,-0.3]$ and $z_t\in[0.36,0.84]$, which are compatible with the $\Lambda$CDM predictions, $q_0=-0.57\pm0.04$, $j_0=-1$ and $z_t=0.71\pm0.08$. We find that even very simple kinematic models are equally good to describe the data compared to the concordance $\Lambda$CDM model, and that the current observations are not powerful enough to discriminate among all of them.Comment: 13 pages. Matches published versio

Megasatellites: a peculiar class of giant minisatellites in genes involved in cell adhesion and pathogenicity in Candida glabrata

Minisatellites are DNA tandem repeats that are found in all sequenced genomes. In the yeast Saccharomyces cerevisiae, they are frequently encountered in genes encoding cell wall proteins. Minisatellites present in the completely sequenced genome of the pathogenic yeast Candida glabrata were similarly analyzed, and two new types of minisatellites were discovered: minisatellites that are composed of two different intermingled repeats (called compound minisatellites), and minisatellites containing unusually long repeated motifs (126–429 bp). These long repeat minisatellites may reach unusual length for such elements (up to 10 kb). Due to these peculiar properties, they have been named ‘megasatellites’. They are found essentially in genes involved in cell–cell adhesion, and could therefore be involved in the ability of this opportunistic pathogen to colonize the human host. In addition to megasatellites, found in large paralogous gene families, there are 93 minisatellites with simple shorter motifs, comparable to those found in S. cerevisiae. Most of the time, these minisatellites are not conserved between C. glabrata and S. cerevisiae, although their host genes are well conserved, raising the question of an active mechanism creating minisatellites de novo in hemiascomycetes

Human candidate gene polymorphisms and risk of severe malaria in children in Kilifi, Kenya: a case-control association study

Background: Human genetic factors are important determinants of malaria risk. We investigated associations between multiple candidate polymorphisms—many related to the structure or function of red blood cells—and risk for severe Plasmodium falciparum malaria and its specific phenotypes, including cerebral malaria, severe malaria anaemia, and respiratory distress. Methods: We did a case-control study in Kilifi County, Kenya. We recruited as cases children presenting with severe malaria to the high-dependency ward of Kilifi County Hospital. We included as controls infants born in the local community between Aug 1, 2006, and Sept 30, 2010, who were part of a genetics study. We tested for associations between a range of candidate malaria-protective genes and risk for severe malaria and its specific phenotypes. We used a permutation approach to account for multiple comparisons between polymorphisms and severe malaria. We judged p values less than 0·005 significant for the primary analysis of the association between candidate genes and severe malaria. Findings: Between June 11, 1995, and June 12, 2008, 2244 children with severe malaria were recruited to the study, and 3949 infants were included as controls. Overall, 263 (12%) of 2244 children with severe malaria died in hospital, including 196 (16%) of 1233 with cerebral malaria. We investigated 121 polymorphisms in 70 candidate severe malaria-associated genes. We found significant associations between risk for severe malaria overall and polymorphisms in 15 genes or locations, of which most were related to red blood cells: ABO, ATP2B4, ARL14, CD40LG, FREM3, INPP4B, G6PD, HBA (both HBA1 and HBA2), HBB, IL10, LPHN2 (also known as ADGRL2), LOC727982, RPS6KL1, CAND1, and GNAS. Combined, these genetic associations accounted for 5·2% of the variance in risk for developing severe malaria among individuals in the general population. We confirmed established associations between severe malaria and sickle-cell trait (odds ratio [OR] 0·15, 95% CI 0·11–0·20; p=2·61 × 10−58), blood group O (0·74, 0·66–0·82; p=6·26 × 10−8), and –α3·7-thalassaemia (0·83, 0·76–0·90; p=2·06 × 10−6). We also found strong associations between overall risk of severe malaria and polymorphisms in both ATP2B4 (OR 0·76, 95% CI 0·63–0·92; p=0·001) and FREM3 (0·64, 0·53–0·79; p=3·18 × 10−14). The association with FREM3 could be accounted for by linkage disequilibrium with a complex structural mutation within the glycophorin gene region (comprising GYPA, GYPB, and GYPE) that encodes for the rare Dantu blood group antigen. Heterozygosity for Dantu was associated with risk for severe malaria (OR 0·57, 95% CI 0·49–0·68; p=3·22 × 10−11), as was homozygosity (0·26, 0·11–0·62; p=0·002). Interpretation: Both ATP2B4 and the Dantu blood group antigen are associated with the structure and function of red blood cells. ATP2B4 codes for plasma membrane calcium-transporting ATPase 4 (the major calcium pump on red blood cells) and the glycophorins are ligands for parasites to invade red blood cells. Future work should aim at uncovering the mechanisms by which these polymorphisms can result in severe malaria protection and investigate the implications of these associations for wider health. Funding: Wellcome Trust, UK Medical Research Council, European Union, and Foundation for the National Institutes of Health as part of the Bill & Melinda Gates Grand Challenges in Global Health Initiative

Analyzing symmetry breaking within a chaotic quantum system via Bayesian inference

Bayesian inference is applied to the level fluctuations of two coupled microwave billiards in order to extract the coupling strength. The coupled resonators provide a model of a chaotic quantum system containing two coupled symmetry classes of levels. The number variance is used to quantify the level fluctuations as a function of the coupling and to construct the conditional probability distribution of the data. The prior distribution of the coupling parameter is obtained from an invariance argument on the entropy of the posterior distribution.Comment: Example from chaotic dynamics. 8 pages, 7 figures. Submitted to PR