Simultaneous Determination of Catechins, Rutin, and Gallic Acid in Cistus Species Extracts by HPLC with Diode Array Detection

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STUDY OF THE O-18+Ni-64 TWO-NEUTRON TRANSFER REACTION AT 84 MeV BY MAGNEX

A study of the two-neutron transfer reaction of the O-18 + Ni-64 system at 84 MeV incident energy to the ground and first 2(+) excited state of the residual Ni-66 nucleus is presented. The experiment was performed at the INFN-LNS (Italy) by using the large acceptance MAGNEX spectrometer. Theoretical models are used in order to disentangle the competition between long-range and short-range correlations

Long-range versus short-range correlations in the two-neutron transfer reaction Ni 64 (O 18, O 16) Ni 66

Recently, various two-neutron transfer studies using the (18O,16O) reaction were performed with a large success. This was achieved because of a combined use of the microscopic quantum description of the reaction mechanism and of the nuclear structure. In the present work we use this methodology to study the two-neutron transfer reaction of the 18O+64Ni system at 84 MeV incident energy, to the ground and first 2+ excited state of the residual 66Ni nucleus. All the experimental data were measured by the large acceptance MAGNEX spectrometer at the Instituto Nazionale di Fisica Nucleare \u2013Laboratori Nazionali del Sud (Italy). We have performed exact finite range cross section calculations using the coupled channel Born approximation (CCBA) and coupled reaction channel (CRC) method for the sequential and direct two-neutron transfers, respectively. Moreover, this is the first time that the formalism of the microscopic interaction boson model (IBM-2) was applied to a two-neutron transfer reaction. From our results we conclude that for two-neutron transfer to the ground state of 66Ni, the direct transfer is the dominant reaction mechanism, whereas for the transfer to the first excited state of 66Ni, the sequential process dominates. A competition between long-range and short-range correlations is discussed, in particular, how the use of two different models (Shell model and IBM's) help to disentangle long- and short-range correlations

Witnessing eigenstates for quantum simulation of Hamiltonian spectra

The efficient calculation of Hamiltonian spectra, a problem often intractable on classical machines, can find application in many fields, from physics to chemistry. Here, we introduce the concept of an "eigenstate witness" and through it provide a new quantum approach which combines variational methods and phase estimation to approximate eigenvalues for both ground and excited states. This protocol is experimentally verified on a programmable silicon quantum photonic chip, a mass-manufacturable platform, which embeds entangled state generation, arbitrary controlled-unitary operations, and projective measurements. Both ground and excited states are experimentally found with fidelities >99%, and their eigenvalues are estimated with 32-bits of precision. We also investigate and discuss the scalability of the approach and study its performance through numerical simulations of more complex Hamiltonians. This result shows promising progress towards quantum chemistry on quantum computers.Comment: 9 pages, 4 figures, plus Supplementary Material [New version with minor typos corrected.

Learning Quantum Systems

Quantum technologies hold the promise to revolutionise our society with ground-breaking applications in secure communication, high-performance computing and ultra-precise sensing. One of the main features in scaling up quantum technologies is that the complexity of quantum systems scales exponentially with their size. This poses severe challenges in the efficient calibration, benchmarking and validation of quantum states and their dynamical control. While the complete simulation of large-scale quantum systems may only be possible with a quantum computer, classical characterisation and optimisation methods (supported by cutting edge numerical techniques) can still play an important role. Here, we review classical approaches to learning quantum systems, their correlation properties, their dynamics and their interaction with the environment. We discuss theoretical proposals and successful implementations in different physical platforms such as spin qubits, trapped ions, photonic and atomic systems, and superconducting circuits. This review provides a brief background for key concepts recurring across many of these approaches, such as the Bayesian formalism or Neural Networks, and outlines open questions

New intravenous calcimimetic agents: New options, new problems. an example on how clinical, economical and ethical considerations affect choice of treatment

Background. Dialysis treatment is improving, but several long-term problems remain unsolved, including metabolic bone disease linked to chronic kidney disease (CKD-MBD). The availability of new, efficacious but expensive drugs (intravenous calcimimetic agents) poses ethical problems, especially in the setting of budget limitations. Methods. Reasons of choice, side effects, biochemical trends were discussed in a cohort of 15 patients (13% of the dialysis population) who stared treatment with intravenous calcimimetics in a single center. All patients had previously been treated with oral calcimimetic agents; dialysis efficacy was at target in 14/15; hemodiafiltration was employed in 10/15. Median Charlson Comorbidity Index was 8. The indications were discussed according to the principlist ethics (beneficience, non maleficience, justice and autonomy). Biochemical results were analyzed to support the clinical-ethical choices. Results. In the context of a strict clinical and biochemical surveillance, the lack of side effects ensured “non-maleficence”; efficacy was at least similar to oral calcimimetic agents, but tolerance was better. Autonomy was respected through a shared decision-making model; all patients appreciated the reduction of the drug burden, and most acknowledged better control of their biochemical data. The ethical conflict resides in the balance between the clinical “beneficience, non-maleficience” advantage and “justice” (economic impact of treatment, potentially in attrition with other resources, since the drug is expensive and included in the dialysis bundle). The dilemma is more relevant when a patient’s life expectancy is short (economic impact without clear clinical advantages), or when non-compliance is an issue (unclear advantage if the whole treatment is not correctly taken). Conclusions. In a context of person-centered medicine, autonomy, beneficence and non-maleficence should weight more than economic justice. While ethical discussions are not aimed at finding “the right answer” but asking “the right questions”, this example can raise awareness of the importance of including an ethical analysis in the choice of “economically relevant” drugs

Experimental Quantum Hamiltonian Learning

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of foundational physics. Machine-learning enhanced by quantum simulators has been proposed as a route to improve the computational cost of performing these studies. Here we interface two different quantum systems through a classical channel - a silicon-photonics quantum simulator and an electron spin in a diamond nitrogen-vacancy centre - and use the former to learn the latter's Hamiltonian via Bayesian inference. We learn the salient Hamiltonian parameter with an uncertainty of approximately $10^{-5}$. Furthermore, an observed saturation in the learning algorithm suggests deficiencies in the underlying Hamiltonian model, which we exploit to further improve the model itself. We go on to implement an interactive version of the protocol and experimentally show its ability to characterise the operation of the quantum photonic device. This work demonstrates powerful new quantum-enhanced techniques for investigating foundational physical models and characterising quantum technologies