22 research outputs found
Phase switching in a voltage-biased Aharonov-Bohm interferometer
Recent experiment [Sigrist et al., Phys. Rev. Lett. {\bf 98}, 036805 (2007)]
reported switches between 0 and in the phase of Aharonov-Bohm
oscillations of the two-terminal differential conductance through a two-dot
ring with increasing voltage bias. Using a simple model, where one of the dots
contains multiple interacting levels, these findings are explained as a result
of transport through the interferometer being dominated at different biases by
quantum dot levels of different "parity" (i.e. the sign of the overlap integral
between the dot state and the states in the leads). The redistribution of
electron population between different levels with bias leads to the fact that
the number of switching events is not necessarily equal to the number of dot
levels, in agreement with experiment. For the same reason switching does not
always imply that the parity of levels is strictly alternating. Lastly, it is
demonstrated that the correlation between the first switching of the phase and
the onset of the inelastic cotunneling, as well as the sharp (rather than
gradual) change of phase when switching occurs, give reason to think that the
present interpretation of the experiment is preferable to the one based on
electrostatic AB effect.Comment: 12 pages, 9 figure
Efficient inference, potential, and limitations of site-specific substitution models
Natural selection imposes a complex filter on which variants persist in a population resulting in evolutionary patterns that vary greatly along the genome. Some sites evolve close to neutrally, while others are highly conserved, allow only specific states, or only change in concert with other sites. On one hand, such constraints on sequence evolution can be to infer biological function, one the other hand they need to be accounted for in phylogenetic reconstruction. Phylogenetic models often account for this complexity by partitioning sites into a small number of discrete classes with different rates and/or state preferences. Appropriate model complexity is typically determined by model selection procedures. Here, we present an efficient algorithm to estimate more complex models that allow for different preferences at every site and explore the accuracy at which such models can be estimated from simulated data. Our iterative approximate maximum likelihood scheme uses information in the data efficiently and accurately estimates site-specific preferences from large data sets with moderately diverged sequences and known topology. However, the joint estimation of site-specific rates, and site-specific preferences, and phylogenetic branch length can suffer from identifiability problems, while ignoring variation in preferences across sites results in branch length underestimates. Site-specific preferences estimated from large HIV; pol; alignments show qualitative concordance with intra-host estimates of fitness costs. Analysis of these substitution models suggests near saturation of divergence after a few hundred years. Such saturation can explain the inability to infer deep divergence times of HIV and SIVs using molecular clock approaches and time-dependent rate estimates
Electron Spin Dynamics in Semiconductors without Inversion Symmetry
We present a microscopic analysis of electron spin dynamics in the presence
of an external magnetic field for non-centrosymmetric semiconductors in which
the D'yakonov-Perel' spin-orbit interaction is the dominant spin relaxation
mechanism. We implement a fully microscopic two-step calculation, in which the
relaxation of orbital motion due to electron-bath coupling is the first step
and spin relaxation due to spin-orbit coupling is the second step. On this
basis, we derive a set of Bloch equations for spin with the relaxation times
T_1 and T_2 obtained microscopically. We show that in bulk semiconductors
without magnetic field, T_1 = T_2, whereas for a quantum well with a magnetic
field applied along the growth direction T_1 = T_2/2 for any magnetic field
strength.Comment: to appear in Proceedings of Mesoscopic Superconductivity and
Spintronics (MS+S2002
In vivo mutation rates and the landscape of fitness costs of HIV-1
Mutation rates and fitness costs of deleterious mutations are difficult to measure in vivo but essential for a quantitative understanding of evolution. Using whole genome deep sequencing data from longitudinal samples during untreated HIV-1 infection, we estimated mutation rates and fitness costs in HIV-1 from the dynamics of genetic variation. At approximately neutral sites, mutations accumulate with a rate of 1.2 Ă— 10(-5) per site per day, in agreement with the rate measured in cell cultures. We estimated the rate from G to A to be the largest, followed by the other transitions C to T, T to C, and A to G, while transversions are less frequent. At other sites, mutations tend to reduce virus replication. We estimated the fitness cost of mutations at every site in the HIV-1 genome using a model of mutation selection balance. About half of all non-synonymous mutations have large fitness costs (>10 percent), while most synonymous mutations have costs <1 percent. The cost of synonymous mutations is especially low in most of pol where we could not detect measurable costs for the majority of synonymous mutations. In contrast, we find high costs for synonymous mutations in important RNA structures and regulatory regions. The intra-patient fitness cost estimates are consistent across multiple patients, indicating that the deleterious part of the fitness landscape is universal and explains a large fraction of global HIV-1 group M diversity
Electron Spin Relaxation in a Semiconductor Quantum Well
A fully microscopic theory of electron spin relaxation by the
D'yakonov-Perel' type spin-orbit coupling is developed for a semiconductor
quantum well with a magnetic field applied in the growth direction of the well.
We derive the Bloch equations for an electron spin in the well and define
microscopic expressions for the spin relaxation times. The dependencies of the
electron spin relaxation rate on the lowest quantum well subband energy,
magnetic field and temperature are analyzed.Comment: Revised version as will appear in Physical Review
Estimating time of HIV-1 infection from next-generation sequence diversity
Estimating the time since infection (TI) in newly diagnosed HIV-1 patients is challenging, but important to understand the epidemiology of the infection. Here we explore the utility of virus diversity estimated by next-generation sequencing (NGS) as novel biomarker by using a recent genome-wide longitudinal dataset obtained from 11 untreated HIV-1-infected patients with known dates of infection. The results were validated on a second dataset from 31 patients. Virus diversity increased linearly with time, particularly at 3rd codon positions, with little inter-patient variation. The precision of the TI estimate improved with increasing sequencing depth, showing that diversity in NGS data yields superior estimates to the number of ambiguous sites in Sanger sequences, which is one of the alternative biomarkers. The full advantage of deep NGS was utilized with continuous diversity measures such as average pairwise distance or site entropy, rather than the fraction of polymorphic sites. The precision depended on the genomic region and codon position and was highest when 3rd codon positions in the entire pol gene were used. For these data, TI estimates had a mean absolute error of around 1 year. The error increased only slightly from around 0.6 years at a TI of 6 months to around 1.1 years at 6 years. Our results show that virus diversity determined by NGS can be used to estimate time since HIV-1 infection many years after the infection, in contrast to most alternative biomarkers. We provide the regression coefficients as well as web tool for TI estimation