In the road towards quantum technologies capable of exploiting the revolutionary potential of quantum theory for information technology, a major bottleneck is the large overhead needed to correct errors caused by unwanted noise. Despite important research activity and great progress in designing better error correcting codes and fault-tolerant schemes, the fundamental limits of communication/computation over a quantum noisy medium are far from being understood. In fact, no satisfactory quantum analogue of Shannon’s celebrated noisy coding theorem is known. The objective of this project is to leverage tools from mathematical optimization in order to build an algorithmic theory of optimal information processing that would go beyond the statistical approach pioneered by Shannon. Our goal will be to establish efficient algorithms that determine optimal methods for achieving a given task, rather than only characterizing the best achievable rates in the asymptotic limit in terms of entropic expressions. This approach will address three limitations — that are particularly severe in the quantum context — faced by the statistical approach: the non-additivity of entropic expressions, the asymptotic nature of the theory and the independence assumption. Our aim is to develop efficient algorithms that take as input a description of a noise model and output a near-optimal method for reliable communication under this model. For example, our algorithms will answer: how many logical qubits can be reliably stored using 100 physical qubits that undergo depolarizing noise with parameter 5%? We will also develop generic and efficient decoding algorithms for quantum error correcting codes. These algorithms will have direct applications to the development of quantum technologies. Moreover, we will establish methods to compute the relevant uncertainty of large structured systems and apply them to obtain tight and non-asymptotic security bounds for (quantum) cryptographic protocols.

Effective EU support to a large external crisis requires new approaches. In response to this challenge and to identified user and market needs from previous projects, Reaching Out proposes an innovative multi-disciplinary approach that will optimize the efforts, address a wide spectrum of users and maximize market innovation success. This approach results in five main objectives: to 1. Develop a Collaborative Framework, with distributed platforms of functional services, 2. Implement a flexible and open “collaborative innovation” process involving users and SMEs, suppliers, operators and research organisations, 3. Develop, upgrade and integrate 78 new connectable and interoperable tools, 4. Conduct 5 large scale demonstrations on the field: o health disaster in Africa (Epidemics in Guinea, with strong social and cultural issues), o natural disaster in a politically complex region and a desert environment (Earthquake in the Jordan Valley, led jointly by Jordan, Israel and Palestine), o three global change disasters in Asia targeted at large evacuation and humanitarian support in Bangladesh (long lasting floods, huge storms and associated epidemics,), EU citizen support and repatriation in Shanghai (floods & storm surge), radiological and industrial disasters impacting EU assets in Taiwan (flash floods, landslides, storm surge and chemical and radiological disasters), supported and co-funded by local authorities, 5. Provide recommendations and evaluations for future legal and policy innovations. The project will be conducted under the supervision of senior end-users. It will be performed with flexible and proven procedures by a balanced consortium of users, industry, innovative SMEs, RTO and academia in the EU and the demonstration regions. The main expected impact is to improve external disaster and crisis management efficiency and cost-benefit and increase the EU visibility whilst enhancing EU industry competitiveness and enlarging the market.

E-CAM will create, develop and sustain a European infrastructure for computational science applied to simulation and modelling of materials and of biological processes of industrial and societal importance. Building on the already significant network of 15 CECAM centres across Europe and the PRACE initiative, it will create a distributed, sustainable centre for simulation and modelling at and across the atomic, molecular and continuum scales. The ambitious goals of E-CAM will be achieved through three complementary instruments: 1. development, testing, maintenance, and dissemination of robust software modules targeted at end-user needs; 2. advanced training of current and future academic and industrial researchers able to exploit these capabilities; 3. multidisciplinary, coordinated, top-level applied consultancy to industrial end-users (both large multinationals and SMEs). The creation and development of this infrastructure will also impact academic research by creating a training opportunity for over 300 researchers in computational science as applied to their domain expertise. It will also provide a structure for the optimisation and long-term maintenance of important codes and provide a route for their exploitation. Based on the requests from its industrial end-users, E-CAM will deliver new software in a broad field by creating over 200 new, robust software modules. The modules will be written to run with maximum efficiency on hardware with different architectures, available at four PRACE centres and at the Hartree Centre for HPC in Industry. The modules will form the core of a software library (the E-CAM library) that will continue to grow and provide benefit well beyond the funding period of the project. E-CAM has a 66 month duration, involves 48 staff years of effort, has a total budget of €5,836,897 and is requesting funding from the EC of €4,836,897, commensurate with achieving its ambitious goals.

Next-Lab intends to change the educational landscape of science and technology education in Europe on a very large scale. The project offers a unique and extensive collection of interactive online (virtual and remote) laboratories that, through a process of mixing and re-use, can be straightforwardly and efficiently combined with dedicated support tools (learning apps) and multimedia material to truly form open, cloud-based, shareable educational resources with an embedded pedagogical structure. Next-Lab offers extensive opportunities for localisation and personalisation together with analytics facilities monitoring students’ progress and achievements. Next-Lab is designed to rely on full co-creation with users in combination with rapid development and testing cycles. Next-Lab builds on the highly successful (FP7) Go-Lab project that already offers online labs, inquiry learning apps, and authoring facilities for inquiry learning. To amplify the existing impact to the next-level innovation stage, Next-Lab extends the Go-Lab system with tools for the learning of 21st century skills, facilities for self- and peer-assessment and portfolio development, as well as opportunities to include learning by modeling. Next-Lab will cover secondary and also primary education, to ensure an early positive attitude towards science and technology and the continuous availability of innovative learning material throughout students' school career. To guarantee long-term impact, Next-Lab also addresses the teachers of the future by its presence in pre-service teacher training programs throughout Europe. To evaluate its impact, Next-Lab combines usage data analysis techniques for very large-scale pilots with in-depth, qualitative, case-based, assessments. Next-Lab prepares for a following sustainable stage of the product. As it builds upon and extends existing networks of teachers, professional associations, and policymakers, the impact of Next-Lab will be massive.

What is the difference between healing and curing? What understandings of wellness, illness and bodies underpin different healing practices? How is therapeutic efficacy assessed in a context of competing valuation practices? This project aims to develop a symmetrical, ethnographically grounded theory of what healing entails from the perspective of those who give, receive or evaluate healing. It is designed to break with binary frames that contrast indigenous and biomedical healing, positioning them on a tradition–modernity continuum. To do this, it will study the striking expansion and prolific reinventions of healing practices that make use of the Amazonian herbal brew ayahuasca. The unprecedented globalization of this indigenous medicine provides a unique opportunity to study healing encounters ethnographically. Through participant observation, interviews, ethnography in expert settings, collaborative workshops and the use of digital methods we will study healing across three related sites: Healing in the City will examine the production of neotraditional urban healing forms. Healing in the Laboratory will analyse how ayahuasca is reinvented as a psychiatric tool to treat mental health problems and Healing in the Forest will study the contemporary reconfigurations of indigenous shamanism. These practices are entangled in long histories of postcolonial encounters: they are all – neotraditional, biomedical and indigenous alike – thoroughly modern and mixed. The comparative analysis is structured around three transversal objectives: 1) Material Semiotics: To develop an innovative framework to map the entanglement of biological and symbolic effects. 2) Encounters Beyond-the-Human: To push medical anthropology beyond the human by paying attention to the healing propitiated by more-than-human beings. 3) Radical Alterity in a Common World of Encounters: To develop an anthropological theory that recognises multiple ontologies without needing to posit multiple worlds.