Reducing Circuit Depth with Qubitwise Diagonalization

A variety of quantum algorithms employ Pauli operators as a convenient basis for studying the spectrum or evolution of Hamiltonians or measuring multi-body observables. One strategy to reduce circuit depth in such algorithms involves simultaneous diagonalization of Pauli operators generating unitary evolution operators or observables of interest. We propose a novel algorithm yielding quantum circuits with depths $\mathcal{O}(n \log r)$ diagonalizing $n$-qubit operators generated by $r$ Pauli operators. Moreover, as our algorithm iteratively diagonalizes all operators on at least one qubit per step, it is well-suited to maintain low circuit depth even on hardware with limited qubit connectivity. We observe that our algorithm performs favorably in producing quantum circuits diagonalizing randomly generated Hamiltonians as well as molecular Hamiltonians with short depths and low two-qubit gate counts.Comment: 10 pages, 3 figure

The yellow European eel (Anguilla anguilla L.) may adopt a sedentary lifestyle in inland freshwaters

We analysed the movements of the growing yellow phase using a long-term mark–recapture programme on European eels in a small catchment (the Frémur, France). The results showed that of the yellow eels (>200 mm) recaptured, more than 90% were recaptured at the original marking site over a long period before the silvering metamorphosis and downstream migration. We conclude that yellow European eels >200 mm may adopt a sedentary lifestyle in freshwater area, especially in small catchment

Inferential Privacy: From Impossibility to Database Privacy

We investigate the possibility of guaranteeing inferential privacy for mechanisms that release useful information about some data containing sensitive information, denoted by $X$. We describe a general model of utility and privacy in which utility is achieved by disclosing the value of low-entropy features of $X$, while privacy is maintained by keeping high-entropy features of $X$ secret. Adopting this model, we prove that meaningful inferential privacy guarantees can be obtained, even though this is commonly considered to be impossible by the well-known result of Dwork and Naor. Then, we specifically discuss a privacy measure called pointwise maximal leakage (PML) whose guarantees are of the inferential type. We use PML to show that differential privacy admits an inferential formulation: it describes the information leaking about a single entry in a database assuming that every other entry is known, and considering the worst-case distribution on the data. Moreover, we define inferential instance privacy (IIP) as a bound on the (non-conditional) information leaking about a single entry in the database under the worst-case distribution, and show that it is equivalent to free-lunch privacy. Overall, our approach to privacy unifies, formalizes, and explains many existing ideas, e.g., why the informed adversary assumption may lead to underestimating the information leaking about each entry in the database. Furthermore, insights obtained from our results suggest general methods for improving privacy analyses; for example, we argue that smaller privacy parameters can be obtained by excluding low-entropy prior distributions from protection

Quantum information and quantum simulation of neutrino physics

In extreme astrophysical environments such as core-collapse supernovae and binary neutron star mergers, neutrinos play a major role in driving various dynamical and microphysical phenomena, such as baryonic matter outflows, the synthesis of heavy elements, and the supernova explosion mechanism itself. The interactions of neutrinos with matter in these environments are flavor-specific, which makes it of paramount importance to understand the flavor evolution of neutrinos. Flavor evolution in these environments can be a highly nontrivial problem thanks to a multitude of collective effects in flavor space, arising due to neutrino-neutrino ($\nu$-$\nu$) interactions in regions with high neutrino densities. A neutrino ensemble undergoing flavor oscillations under the influence of significant $\nu$-$\nu$ interactions is somewhat analogous to a system of coupled spins with long-range interactions among themselves and with an external field ('long-range' in momentum-space in the case of neutrinos). As a result, it becomes pertinent to consider whether these interactions can give rise to significant quantum correlations among the interacting neutrinos, and whether these correlations have any consequences for the flavor evolution of the ensemble. In particular, one may seek to utilize concepts and tools from quantum information science and quantum computing to deepen our understanding of these phenomena. In this article, we attempt to summarize recent work in this field. Furthermore, we also present some new results in a three-flavor setting, considering complex initial states.Comment: 13 pages, 3 figures. Invited review for the Eur. Phys. J. A special issue on "Quantum computing in low-energy nuclear theory

Continuous population-level monitoring of SARS-CoV-2 seroprevalence in a large European metropolitan region.

Effective public health measures against SARS-CoV-2 require granular knowledge of population-level immune responses. We developed a Tripartite Automated Blood Immunoassay (TRABI) to assess the IgG response against three SARS-CoV-2 proteins. We used TRABI for continuous seromonitoring of hospital patients and blood donors (n = 72'250) in the canton of Zurich from December 2019 to December 2020 (pre-vaccine period). We found that antibodies waned with a half-life of 75 days, whereas the cumulative incidence rose from 2.3% in June 2020 to 12.2% in mid-December 2020. A follow-up health survey indicated that about 10% of patients infected with wildtype SARS-CoV-2 sustained some symptoms at least twelve months post COVID-19. Crucially, we found no evidence of a difference in long-term complications between those whose infection was symptomatic and those with asymptomatic acute infection. The cohort of asymptomatic SARS-CoV-2-infected subjects represents a resource for the study of chronic and possibly unexpected sequelae