Spin-based quantum information processing with semiconductor quantum dots and cavity QED

A quantum information processing scheme is proposed with semiconductor quantum dots located in a high-Q single mode QED cavity. The spin degrees of freedom of one excess conduction electron of the quantum dots are employed as qubits. Excitonic states, which can be produced ultrafastly with optical operation, are used as auxiliary states in the realization of quantum gates. We show how properly tailored ultrafast laser pulses and Pauli-blocking effects, can be used to achieve a universal encoded quantum computing.Comment: RevTex, 2 figure

Some peculiarities of motion of neutral and charged test particles in the field of a spherically symmetric charged object in General Relativity

We propose the method of investigation of radial motions for charged and neutral test particles in the Reissner-Nordstr\"{o}m field by means of mass potential. In this context we analyze special features of interaction of charges and their motions in General Relativity and construct the radial motion classification. For test particles and a central source with charges $q$ and $Q$, respectively, the conditions of attraction (when $qQ>0$) and repulsion (when $qQ<0$) are obtained. The conditions of motionless test particle states with respect to the central source are investigated and, in addition, stability conditions for such static equilibrium states are found. It is shown that stable states are possible only for the bound states of weakly charged particles in the field of a naked singularity. Frequencies of small oscillations of test particles near their equilibrium positions are also found.Comment: 15 pages, 9 figure

Sub-microsecond correlations in photoluminescence from InAs quantum dots

Photon correlation measurements reveal memory effects in the optical emission of single InAs quantum dots with timescales from 10 to 800 ns. With above-band optical excitation, a long-timescale negative correlation (antibunching) is observed, while with quasi-resonant excitation, a positive correlation (blinking) is observed. A simple model based on long-lived charged states is presented that approximately explains the observed behavior, providing insight into the excitation process. Such memory effects can limit the internal efficiency of light emitters based on single quantum dots, and could also be problematic for proposed quantum-computation schemes.Comment: 8 pages, 8 figure

First Observation of Coherent π0\pi^0 Production in Neutrino Nucleus Interactions with Eν<E_{\nu}< 2 GeV

The MiniBooNE experiment at Fermilab has amassed the largest sample to date of $\pi^0$s produced in neutral current (NC) neutrino-nucleus interactions at low energy. This paper reports a measurement of the momentum distribution of $\pi^0$s produced in mineral oil (CH$_2$) and the first observation of coherent $\pi^0$ production below 2 GeV. In the forward direction, the yield of events observed above the expectation for resonant production is attributed primarily to coherent production off carbon, but may also include a small contribution from diffractive production on hydrogen. Integrated over the MiniBooNE neutrino flux, the sum of the NC coherent and diffractive modes is found to be (19.5 $\pm$1.1 (stat) $\pm$2.5 (sys))% of all exclusive NC $\pi^0$ production at MiniBooNE. These measurements are of immediate utility because they quantify an important background to MiniBooNE's search for $\nu_{\mu} \to \nu_e$ oscillations.Comment: Submitted to Phys. Lett.

A Two-Dimensional Electron Gas as a Sensitive Detector for Time-Resolved Tunneling Measurements on Self-Assembled Quantum Dots

A two-dimensional electron gas (2DEG) situated nearby a single layer of self-assembled quantum dots (QDs) in an inverted high electron mobility transistor (HEMT) structure is used as a detector for time-resolved tunneling measurements. We demonstrate a strong influence of charged QDs on the conductance of the 2DEG which allows us to probe the tunneling dynamics between the 2DEG and the QDs time resolved. Measurements of hysteresis curves with different sweep times and real-time conductance measurements in combination with an boxcar-like evaluation method enables us to unambiguously identify the transients as tunneling events between the s- and p-electron QD states and the 2DEG and rule out defect-related transients

Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.Peer Reviewe

Test of Lorentz and CPT violation with Short Baseline Neutrino Oscillation Excesses

The sidereal time dependence of MiniBooNE electron neutrino and anti-electron neutrino appearance data are analyzed to search for evidence of Lorentz and CPT violation. An unbinned Kolmogorov-Smirnov test shows both the electron neutrino and anti-electron neutrino appearance data are compatible with the null sidereal variation hypothesis to more than 5%. Using an unbinned likelihood fit with a Lorentz-violating oscillation model derived from the Standard Model Extension (SME) to describe any excess events over background, we find that the electron neutrino appearance data prefer a sidereal time-independent solution, and the anti-electron neutrino appearance data slightly prefer a sidereal time-dependent solution. Limits of order 10E-20 GeV are placed on combinations of SME coefficients. These limits give the best limits on certain SME coefficients for muon neutrino to electron neutrino and anti-muon neutrino to anti-electron neutrino oscillations. The fit values and limits of combinations of SME coefficients are provided.Comment: 14 pages, 3 figures, and 2 tables, submitted to Physics Letters

Effects of Intermittent IL-2 Alone or with Peri-Cycle Antiretroviral Therapy in Early HIV Infection: The STALWART Study

The Study of Aldesleukin with and without antiretroviral therapy (STALWART) evaluated whether intermittent interleukin-2 (IL-2) alone or with antiretroviral therapy (ART) around IL-2 cycles increased CD4+ counts compared to no therapy

Neutrino oscillation studies with IceCube-DeepCore

AbstractIceCube, a gigaton-scale neutrino detector located at the South Pole, was primarily designed to search for astrophysical neutrinos with energies of PeV and higher. This goal has been achieved with the detection of the highest energy neutrinos to date. At the other end of the energy spectrum, the DeepCore extension lowers the energy threshold of the detector to approximately 10 GeV and opens the door for oscillation studies using atmospheric neutrinos. An analysis of the disappearance of these neutrinos has been completed, with the results produced being complementary with dedicated oscillation experiments. Following a review of the detector principle and performance, the method used to make these calculations, as well as the results, is detailed. Finally, the future prospects of IceCube-DeepCore and the next generation of neutrino experiments at the South Pole (IceCube-Gen2, specifically the PINGU sub-detector) are briefly discussed

A muon-track reconstruction exploiting stochastic losses for large-scale Cherenkov detectors

IceCube is a cubic-kilometer Cherenkov telescope operating at the South Pole. The main goal of IceCube is the detection of astrophysical neutrinos and the identification of their sources. High-energy muon neutrinos are observed via the secondary muons produced in charge current interactions with nuclei in the ice. Currently, the best performing muon track directional reconstruction is based on a maximum likelihood method using the arrival time distribution of Cherenkov photons registered by the experiment\u27s photomultipliers. A known systematic shortcoming of the prevailing method is to assume a continuous energy loss along the muon track. However at energies >1 TeV the light yield from muons is dominated by stochastic showers. This paper discusses a generalized ansatz where the expected arrival time distribution is parametrized by a stochastic muon energy loss pattern. This more realistic parametrization of the loss profile leads to an improvement of the muon angular resolution of up to 20% for through-going tracks and up to a factor 2 for starting tracks over existing algorithms. Additionally, the procedure to estimate the directional reconstruction uncertainty has been improved to be more robust against numerical errors