A new U.S. record for a secondary fruit infester, Neosilba baresi (Curran) (Diptera: Lonchaeidae)

A lonchaeid fly, Neosilba batesi, first described by Curran in 1932 from Guatemala, is here reported in Florida as of September 1994, a new U.S. record

An annotated checklist of the Tephritidae (Diptera) of Florida

A total of 73 species of tephritid flies has been recorded from Florida since the early 1800s. Of these, 7 species are considered to represent occasional waifs or accidental introductions from surrounding regions that are not known to have established populations in Florida; 6 are exotic pests which failed to colonize or were extirpated; and 7 species are represented only by early literature records and are considered dubious for the state. Thus, the tephritid fauna of Florida currently comprises a total of 53 species of which 1 species is precinctive to the state and considered to be endangered

A quantum neural network computes its own relative phase

Complete characterization of the state of a quantum system made up of subsystems requires determination of relative phase, because of interference effects between the subsystems. For a system of qubits used as a quantum computer this is especially vital, because the entanglement, which is the basis for the quantum advantage in computing, depends intricately on phase. We present here a first step towards that determination, in which we use a two-qubit quantum system as a quantum neural network, which is trained to compute and output its own relative phase

New records for Tephritidae (Diptera) in Great Smoky Mountains National Park

As part of the All Taxon Biological Inventory (ATBI) being conducted in the Great Smoky Mountains National Park (GSMNP), we report new distribution and host plant records for nine Tephritidae species

New records of Tephritidae (Diptera) from Great Smoky Mountains National Park - 2

Thirty additional species of tephritid flies (Diptera: Tephritidae) from Great Smoky Mountains National Park (GSMNP), including historical records, are presented together with information on host(s), if known, distributions, and life histories. This brings the total number of tephritid flies recorded from GSMNP to 46

Structural and dynamical aspects of avoided-crossing resonances in a 33-level Λ\Lambda system

In a recent publication [Phys. Rev. A 79, 065602 (2009)] it was shown that an avoided-crossing resonance can be defined in different ways, according to level-structural or dynamical aspects, which do not coincide in general. Here a simple $3$-level system in a $\Lambda$ configuration is discussed, where the difference between both definitions of the resonance may be observed. We also discuss the details of a proposed experiment to observe this difference, using microwave fields coupling hyperfine magnetic sublevels in alkali atoms.Comment: 7 pages, 5 figure

Isospin forbidden and allowed reactions \u3csup\u3e16\u3c/sup\u3eO(\u3ci\u3eα\u3c/i\u3e,\u3ci\u3eα\u3c/i\u3e\u3csub\u3e0\u3c/sub\u3e)\u3csup\u3e16\u3c/sup\u3e0 and \u3csup\u3e16\u3c/sup\u3e0(\u3ci\u3eα\u3c/i\u3e,\u3ci\u3eγ\u3c/i\u3e)\u3csup\u3e20\u3c/sup\u3eNe

Six 20Ne levels have been investigated in detail via the 16O+α channel between 6.9≤Eα≤10.2 MeV. Level parameters for states at Ex(20Ne)=10.264±0.008, 11.077±0.008, 11.259±0.008, 11.552±0.008,12.237±0.008, and 12.390±0.008 MeV have been extracted from γ decay properties and phase shift analysis of the elastic scattering. With the exception of the 11.552 and 12.39 MeV states, these levels display primarily TT=0 states, several other weak γ decaying resonances were observed at 11.97 ± 0.04, 12.05 ± 0.04, and 12.49 ± 0.02 MeV but were not studied in detail. Charge dependent matrix elements (4-120 keV) for isospin mixing of T=1 states with nearby T=0 states were estimated from the measured level parameters

On the correction of anomalous phase oscillation in entanglement witnesses using quantum neural networks

Entanglement of a quantum system depends upon relative phase in complicated ways, which no single measurement can reflect. Because of this, entanglement witnesses are necessarily limited in applicability and/or utility. We propose here a solution to the problem using quantum neural networks. A quantum system contains the information of its entanglement; thus, if we are clever, we can extract that information efficiently. As proof of concept, we show how this can be done for the case of pure states of a two-qubit system, using an entanglement indicator corrected for the anomalous phase oscillation. Both the entanglement indicator and the phase correction are calculated by the quantum system itself acting as a neural network