12,650 research outputs found
Full-counting statistics of charge and spin transport in the transient regime: A nonequilibrium Green's function approach
We report the investigation of full-counting statistics (FCS) of transferred
charge and spin in the transient regime where the connection between central
scattering region (quantum dot) and leads are turned on at . A general
theoretical formulation for the generating function (GF) is presented using a
nonequilibrium Green's function approach for the quantum dot system. In
particular, we give a detailed derivation on how to use the method of path
integral together with nonequilibrium Green's function technique to obtain the
GF of FCS in electron transport systems based on the two-time quantum
measurement scheme. The correct long-time limit of the formalism, the
Levitov-Lesovik's formula, is obtained. This formalism can be generalized to
account for spin transport for the system with noncollinear spin as well as
spin-orbit interaction. As an example, we have calculated the GF of
spin-polarized transferred charge, transferred spin, as well as the spin
transferred torque for a magnetic tunneling junction in the transient regime.
The GF is compactly expressed by a functional determinant represented by
Green's function and self-energy in the time domain. With this formalism, FCS
in spintronics in the transient regime can be studied. We also extend this
formalism to the quantum point contact system. For numerical results, we
calculate the GF and various cumulants of a double quantum dot system connected
by two leads in transient regime. The signature of universal oscillation of FCS
is identified. On top of the global oscillation, local oscillations are found
in various cumulants as a result of the Rabi oscillation. Finally, the
influence of the temperature is also examined
Exploiting Amplitude Control in Intelligent Reflecting Surface Aided Wireless Communication with Imperfect CSI
Intelligent reflecting surface (IRS) is a promising new paradigm to achieve
high spectral and energy efficiency for future wireless networks by
reconfiguring the wireless signal propagation via passive reflection. To reap
the potential gains of IRS, channel state information (CSI) is essential,
whereas channel estimation errors are inevitable in practice due to limited
channel training resources. In this paper, in order to optimize the performance
of IRS-aided multiuser systems with imperfect CSI, we propose to jointly design
the active transmit precoding at the access point (AP) and passive reflection
coefficients of IRS, each consisting of not only the conventional phase shift
and also the newly exploited amplitude variation. First, the achievable rate of
each user is derived assuming a practical IRS channel estimation method, which
shows that the interference due to CSI errors is intricately related to the AP
transmit precoders, the channel training power and the IRS reflection
coefficients during both channel training and data transmission. Then, for the
single-user case, by combining the benefits of the penalty method, Dinkelbach
method and block successive upper-bound minimization (BSUM) method, a new
penalized Dinkelbach-BSUM algorithm is proposed to optimize the IRS reflection
coefficients for maximizing the achievable data transmission rate subjected to
CSI errors; while for the multiuser case, a new penalty dual decomposition
(PDD)-based algorithm is proposed to maximize the users' weighted sum-rate.
Simulation results are presented to validate the effectiveness of our proposed
algorithms as compared to benchmark schemes. In particular, useful insights are
drawn to characterize the effect of IRS reflection amplitude control
(with/without the conventional phase shift) on the system performance under
imperfect CSI.Comment: 15 pages, 10 figures, accepted by IEEE Transactions on Communication
Statistical Mechanical Treatments of Protein Amyloid Formation
Protein aggregation is an important field of investigation because it is
closely related to the problem of neurodegenerative diseases, to the
development of biomaterials, and to the growth of cellular structures such as
cyto-skeleton. Self-aggregation of protein amyloids, for example, is a
complicated process involving many species and levels of structures. This
complexity, however, can be dealt with using statistical mechanical tools, such
as free energies, partition functions, and transfer matrices. In this article,
we review general strategies for studying protein aggregation using statistical
mechanical approaches and show that canonical and grand canonical ensembles can
be used in such approaches. The grand canonical approach is particularly
convenient since competing pathways of assembly and dis-assembly can be
considered simultaneously. Another advantage of using statistical mechanics is
that numerically exact solutions can be obtained for all of the thermodynamic
properties of fibrils, such as the amount of fibrils formed, as a function of
initial protein concentration. Furthermore, statistical mechanics models can be
used to fit experimental data when they are available for comparison.Comment: Accepted to IJM
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