Related papers: Effective Hamiltonian based DNP Sequence Optimizat…
Nuclear magnetic resonance spectroscopy with solid-state spin sensors is a promising pathway for the detection of nuclear spins at the micro- and nanoscale. Although many nanoscale experiments rely on a single sensor spin for the detection…
Purpose -- RF circuits often possess a multi-rate behavior. Slow changing baseband signals and fast oscillating carrier signals often occur in the same circuit. Frequency modulated signals pose a particular challenge.…
The nuclear spins in nanostructured semiconductors play a central role in quantum applications. The nuclear spins represent a useful resource for generating local magnetic fields but nuclear spin noise represents a major source of dephasing…
Coupled pairs of spin-1/2 nuclei support one singlet state and three triplet states. In many circumstances the nuclear singlet order, defined as the difference between the singlet population and the mean of the triplet populations, is a…
Collective optical excitations in dipole-coupled nanorings of sub-wavelength spaced quantum emitters exhibit extreme sub-radiance and field confinement facilitating an efficient and low-loss ring-to-ring energy transfer. We show that energy…
It was recently demonstrated that bulk nuclear polarization can be obtained using Nitrogen Vacancy (NV) color centers in diamonds, even at ambient conditions. This is based on the optical polarization of the NV electron spin, and using…
We report on the dynamics of optically induced nuclear spin polarization in individual CdTe/ZnTe quantum dots loaded with one electron by modulation doping. The fine structure of the hot trion (charged exciton $X^-$ with an electron in the…
Nuclear magnetic resonance (NMR) schemes can be applied to micron-, and nanometer-sized samples by the aid of quantum sensors such as nitrogen-vacancy (NV) color centers in diamond. These minute devices allow for magnetometry of nuclear…
In a dynamic nuclear polarization experiment on a 40 mM solution of 4-amino-TEMPO in a 40:60 water/glycerol mixture, we have observed that the bulk dipolar reservoir is cooled to a spin temperature of 15.5 micro-K, following microwave…
Over the last two decades magic angle spinning dynamic nuclear polarization (MAS DNP) has revolutionized NMR for materials characterization, tackling its main limitation of intrinsically low sensitivity. Progress in theoretical…
We report a large enhancement of 1.7 in deuteron polarization up to values of 0.6 due to frequency modulation of the polarizing microwaves in a two liters polarized target using the method of dynamic nuclear polarization. This target was…
Nuclear-spin diffusion in double quantum wells (QWs) is examined by using dynamic nuclear polarization (DNP) at a Landau level filling factor $\nu=2/3$ spin phase transition (SPT). The longitudinal resistance increases during the DNP of one…
High-fidelity multi-qubit initialization is vital for quantum simulation, quantum information processing (QIP), and quantum sensing. In diamond platforms, nuclear spin registers can be initialized through polarization transfer from a nearby…
Magnetic resonance imaging at microtesla fields is a promising imaging method that combines the pre-polarization technique and broadband signal reception by SQUID sensors to enable in vivo MRI at microtesla-range magnetic fields. Despite…
We report polarization of a dense nuclear-spin ensemble in diamond and its dependence on magnetic field and temperature. The polarization method is based on the transfer of electron spin polarization of negatively charged nitrogen vacancy…
In this article we address the general approach for calculating dynamical dipole polarizabilities of small quantum systems, based on a sum-over-states formula involving in principle the entire energy spectrum of the system. We complement…
Optical neural networks (ONNs) perform extensive computations using photons instead of electrons, resulting in passively energy-efficient and low-latency computing. Among various ONNs, the diffractive optical neural networks (DONNs)…
Deep neural networks (DNNs) play an important role in machine learning due to its outstanding performance compared to other alternatives. However, DNNs are not suitable for safety-critical applications since DNNs can be easily fooled by…
Periodically driven Floquet quantum systems provide a promising platform to investigate novel physics out of equilibrium. Unfortunately, the drive generically heats up the system to a featureless infinite temperature state. For large…
In this work, we propose an effective scheme (called DP-Net) for compressing the deep neural networks (DNNs). It includes a novel dynamic programming (DP) based algorithm to obtain the optimal solution of weight quantization and an…