Quantum digital cooling

We introduce a method for digital preparation of ground states of a simulated Hamiltonians, inspired by cooling in nature and adapted to leverage the capabilities of digital quantum hardware. The cold bath is simulated by a single ancillary qubit, which is reset periodically and coupled to the system non-perturbatively. Studying this cooling method on a 1-qubit system toy model allows us to optimize two cooling protocols based on weak-coupling and strong-coupling approaches. Extending the insight from the 1-qubit system model, we develop two scalable protocols for larger systems. The LogSweep protocol extends the weak-coupling approach by sweeping energies to resonantly match any targeted transition. It demonstrates the ability to prepare an approximate ground state of tranverse-field Ising chains in the ferromangetic and critical phases, with an error that can be made polynomially small in time. The BangBang protocol extends the strong-coupling approach, and exploits a heuristics for local Hamiltonians to maximise the probability of de-exciting system transitions in the shortest possible time. Although this protocol does not promise long-time convergence, it allows for a rapid cooling to an approximation of the ground state, making this protocol appealing for near-term simulation applications.Comment: 8 pages, 8 figure

Optimizing the information extracted by a single qubit measurement

We consider a quantum computation that only extracts one bit of information per quantum state preparation. This is relevant for error mitigation schemes where the remainder of the system is measured to detect errors. We optimize the estimation of the expectation value of an operator by its linear decomposition into bitwise-measurable terms. We prove that optimal decompositions must be in terms of reflections with eigenvalues $\pm1$. We find the optimal reflection decomposition of a fast-forwardable operator, and show a numerical improvement over a simple Pauli decomposition by a factor $N^{0.7}$.Comment: 14 pages, 4 figure

Virtual mitigation of coherent non-adiabatic transitions by echo verification

Transitions out of the ground space limit the performance of quantum adiabatic algorithms, while hardware imperfections impose stringent limitations on the circuit depth. We propose an adiabatic echo verification protocol which mitigates both coherent and incoherent errors, arising from non-adiabatic transitions and hardware noise, respectively. Quasi-adiabatically evolving forward and backwards allows for an echo-verified measurement of any observable. In addition to mitigating hardware noise, our method uses positive-time dynamics only. Crucially, the estimator bias of the observable is reduced when compared to standard adiabatic preparation, achieving up to a quadratic improvement.Comment: 10 pages, 3 figure

Towards a Timely Prediction of Earthquake Intensity with Social Media

A growing number of people is turning to Social Media in the aftermath of emergencies to search and publish critical and up to date information. Retrieval and exploitation of such information may prove crucial to decision makers in order to minimize the impact of disasters on the population and the infrastructures. Yet, to date, the task of the automatic assessment of the consequences of disasters has received little to no attention. Our work aims to bridge this gap, merging the theory behind statistical learning and predictive models with the data behind social media. Here we investigate the exploitation of Twitter data for the improvement of earthquake emergency management. We adopt a set of predictive linear models and evaluate their ability to map the intensity of worldwide earthquakes. The models build on a dataset of almost 5 million tweets and more than 7,000 globally distributed earthquakes. We run and discuss diagnostic tests and simulations on generated models to assess their significance and avoid overfitting. Finally we deal with the interpretation of the relations uncovered by the linear models and we conclude by illustrating how findings reported in this work can be leveraged by existing emergency management systems. Overall results show the effectiveness of the proposed techniques and allow to obtain an estimation of the earthquake intensity far earlier than conventional methods do. The employment of the proposed solutions can help understand scenarios where damage actually occurred in order to define where to concentrate the rescue teams and organize a prompt emergency response

Nowcasting of Earthquake Consequences Using Big Social Data

Messages posted to social media in the aftermath of a natural disaster have value beyond detecting the event itself. Mining such deliberately dropped digital traces allows a precise situational awareness, to help provide a timely estimate of the disaster’s consequences on the population and infrastructures. Yet, to date, the automatic assessment of damage has received little attention. Here, the authors explore feeding predictive models by tweets conveying on-the-ground social sensors’ observations, to nowcast the perceived intensity of earthquakes

A hybrid quantum algorithm to detect conical intersections

Conical intersections are topologically protected crossings between the potential energy surfaces of a molecular Hamiltonian, known to play an important role in chemical processes such as photoisomerization and non-radiative relaxation. They are characterized by a non-zero Berry phase, which is a topological invariant defined on a closed path in atomic coordinate space, taking the value $\pi$ when the path encircles the intersection manifold. In this work, we show that for real molecular Hamiltonians, the Berry phase can be obtained by tracing a local optimum of a variational ansatz along the chosen path and estimating the overlap between the initial and final state with a control-free Hadamard test. Moreover, by discretizing the path into $N$ points, we can use $N$ single Newton-Raphson steps to update our state non-variationally. Finally, since the Berry phase can only take two discrete values (0 or $\pi$), our procedure succeeds even for a cumulative error bounded by a constant; this allows us to bound the total sampling cost and to readily verify the success of the procedure. We demonstrate numerically the application of our algorithm on small toy models of the formaldimine molecule (\ce{H2C=NH}).Comment: 15 + 10 pages, 4 figure

Replica 55 Project: aerodynamic and fem analysis of a wooden seaplane

The engineering approach and the technical contents of an aeronautical design project is presented as the result of a students team work at their last year of bachelor’s degree at Polytechnic of Turin (Italy). Starting from a complete wooden seaplane, the Savoia Marchetti S55, aerodynamic, flight mechanics and structural analysis were performed and investigated in detail. From the point of view of structural modeling, the obtained results present how a natural composite material such as wood, can be treated as the latest generation composite materials adopted in aeronautical constructions

The earlier, the better: Impact of early diagnosis on clinical outcome in idiopathic pulmonary fibrosis

Background Idiopathic pulmonary fibrosis (IPF) is a complex disease with a highly variable clinical course and generally poor prognosis. Classified as a rare disease, significant increases in incidence have been recorded worldwide in recent years. Left untreated IPF is extremely debilitating with substantial personal, social and economic implications. Objectives To discuss how IPF is diagnosed and managed in real life clinical practice with particular reference to Italy and to determine how new and effective therapies can be incorporated into a patient-centred management approach in order to improve the lives of patients with IPF. Outcomes Barriers to early diagnosis are discussed. Cited reasons for delays in diagnosing IPF in Italy include: inherent difficulties in diagnosis; lack of knowledge/awareness of the condition among point-of-contact healthcare professionals; delays in referral to centres of excellence and underestimation of symptoms by both patients and healthcare workers. Valid therapeutic options with demonstrated efficacy in slowing the decline in lung function are now available for patients with IPF. The ASCEND trial confirmed the effects of pirfenidone, approved for the treatment of IPF on the basis of the four phase III trials. Nintedanib, a tyrosine kinase inhibitor that targets the PDGF receptors α/β, FGF receptors 1 to 3, and VEGF receptors 1–3, is approved in the USA and the EU for the treatment of IPF. The TOMORROW and the INPULSIS placebo controlled trials in patients with IPF confirm the efficacy and safety of nintedanib and recent interim analyses endorse its long-term effects in slowing disease progression. Conclusions The importance of early and accurate diagnosis of IPF cannot be underestimated and it is the duty of all healthcare professionals to be vigilant to the symptoms of IPF and to involve a multidisciplinary team in diagnosing and managing IPF early in the course of disease