Related papers: Designing broadband pulsed dynamic nuclear polariz…
Quantum emitters in solid-state crystals have recently attracted a lot of attention due to their simple applicability in optical quantum technologies. The polarization of single photons generated by quantum emitters is one of the key…
This thesis develops a general theoretical and numerical framework for achieving high-contrast atom interferometry based on double Bragg diffraction (DBD). While DBD offers intrinsic symmetry, reduced sensitivity to internal-state…
We develop theoretically and demonstrate experimentally a universal dynamical decoupling method for robust quantum sensing with unambiguous signal identification. Our method uses randomisation of control pulses to suppress simultaneously…
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…
The paper describes the design of band selective excitation and rotation pulses in high resolution NMR by method of double sweep. We first show the design of a pulse sequence that produces band selective excitation to the equator of Bloch…
In this work we developed a method for simulating polar species in the dissipative particle dynamics (DPD) method. The main idea behind the method is to treat each bead as a dumb-bell, i.e. two sub-beads (the sub-beads can bear charges)…
We use dynamic nuclear polarization (DNP) enhanced nuclear magnetic resonance (NMR) at liquid helium temperatures to directly detect hydrogen attached to the surface of silicon microparticles. The proton NMR spectrum from a dry sample of…
This is a methodological guide to the use of deep neural networks in the processing of pulsed dipolar spectroscopy (PDS) data encountered in structural biology, organic photovoltaics, photosynthesis research, and other domains featuring…
Dynamic signed networks (DSNs) are common in online platforms, where time-stamped positive and negative relations evolve over time. A core task in DSNs is dynamic edge prediction, which forecasts future relations by jointly modeling edge…
The interaction of condensed phase systems with external electric fields is crucial in myriad processes in nature and technology ranging from the field-directed motion of cells (galvanotaxis), to energy storage and conversion systems…
Compared to the conventional metasurface design, machine learning-based methods have recently created an inspiring platform for an inverse realization of the metasurfaces. Here, we have used the Deep Neural Network (DNN) for the generation…
We present a novel microplasma flow reactor using a dielectric barrier discharge (DBD) driven by repetitively nanosecond high-voltage pulses. Our DBD-based geometry can generate a non-thermal plasma discharge at atmospheric pressure and…
Diffractive deep neural network (DNNet) is a novel machine learning framework on the modulation of optical transmission. Diffractive network would get predictions at the speed of light. It's pure passive architecture, no additional power…
In this paper, we numerically optimize broadband pulse shapes that maximize Hahn echo amplitudes. Pulses are parameterized as neural networks (NN), nonlinear amplitude limited Fourier series (FS), and discrete time series (DT). These are…
The central-spin problem, in which an electron spin interacts with a nuclear spin bath, is a widely studied model of quantum decoherence. Dynamic nuclear polarization (DNP) occurs in central spin systems when electronic angular momentum is…
Microwave(MW) fields with strong field strength, ultralow phase-noise and tunable polarization are crucial for stabilizing and manipulating ultracold polar molecules, which have emerged as a promising platform for quantum sciences. In this…
Digital back-propagation (DBP) and learned DBP (LDBP) are proposed for nonlinearity mitigation in WDM dual-polarization dispersion-managed systems. LDBP achieves Q-factor improvement of 1.8 dB and 1.2 dB, respectively, over linear…
The sensitivity of Magnetic Resonance Imaging (MRI) depends strongly on nuclear spin polarisation and, motivated by this observation, dynamical nuclear spin polarisation has recently been applied to enhance MRI protocols (Kurhanewicz, J.,…
We introduce a general technique to generate compressed broadband terahertz pulses based on difference frequency generation of optical pump radiation using aperiodically poled structures. The pump pulse format and poling of the crystals…
Early experiments on spin-blockaded double quantum dots revealed surprising robust, large-amplitude current oscillations in the presence of a static (dc) source-drain bias [see e.g. K. Ono, S. Tarucha, Phys. Rev. Lett. 92, 256803 (2004)].…