No Arabic abstract
The optical selection rules in epitaxial quantum dots are strongly influenced by the orientation of their natural quantization axis, which is usually parallel to the growth direction. This configuration is well suited for vertically emitting devices, but not for planar photonic circuits because of the poorly controlled orientation of the transition dipoles in the growth plane. Here we show that the quantization axis of gallium arsenide dots can be flipped into the growth plane via moderate in plane uniaxial stress. By using piezoelectric strain actuators featuring strain-amplification we study the evolution of the selection rules and excitonic fine-structure in a regime, in which quantum confinement can be regarded as a perturbation compared to strain in determining the symmetry properties of the system. The experimental and computational results suggest that uniaxial stress, may be the right tool to obtain quantum light sources with ideally oriented transition dipoles and enhanced oscillator strengths for integrated quantum photonics.
Wave mixing is an archetypical phenomenon in bosonic systems. In optomechanics, the bi-directional conversion between electromagnetic waves or photons at optical frequencies and elastic waves or phonons at radio frequencies is building on precisely this fundamental principle. Surface acoustic waves provide a versatile interconnect on a chip and, thus, enable the optomechanical control of remote systems. Here, we report on the coherent nonlinear three-wave mixing between the coherent fields of two radio frequency surface acoustic waves and optical laser photons via the dipole transition of a single quantum dot exciton. In the resolved sideband regime, we demonstrate fundamental acoustic analogues of sum and difference frequency generation between the two SAWs and employ phase matching to deterministically enhance or suppress individual sidebands. This bi-directional transfer between the acoustic and optical domains is described by theory which fully takes into account direct and virtual multi-phonon processes. Finally, we show that the precision of the wave mixing is limited by the frequency accuracy of modern radio frequency electronics.
Electron spins in Si are an attractive platform for quantum computation, backed with their scalability and fast, high-fidelity quantum logic gates. Despite the importance of two-dimensional integration with efficient connectivity between qubits for medium- to large-scale quantum computation, however, a practical device design that guarantees qubit addressability is yet to be seen. Here, we propose a practical 3 x 3 quantum dot device design and a larger-scale design as a longer-term target. The design goal is to realize qubit connectivity to the four nearest neighbors while ensuring addressability. We show that a 3 x 3 quantum dot array can execute four-qubit Grovers algorithm more efficiently than the one-dimensional counterpart. To scale up the two-dimensional array beyond 3 x 3, we propose a novel structure with ferromagnetic gate electrodes. Our results showcase the possibility of medium-sized quantum processors in Si with fast quantum logic gates and long coherence times.
Current density distributions in active integrated circuits (ICs) result in patterns of magnetic fields that contain structural and functional information about the IC. Magnetic fields pass through standard materials used by the semiconductor industry and provide a powerful means to fingerprint IC activity for security and failure analysis applications. Here, we demonstrate high spatial resolution, wide field-of-view, vector magnetic field imaging of static (DC) magnetic field emanations from an IC in different active states using a Quantum Diamond Microscope (QDM). The QDM employs a dense layer of fluorescent nitrogen-vacancy (NV) quantum defects near the surface of a transparent diamond substrate placed on the IC to image magnetic fields. We show that QDM imaging achieves simultaneous $sim10$ $mu$m resolution of all three vector magnetic field components over the 3.7 mm $times$ 3.7 mm field-of-view of the diamond. We study activity arising from spatially-dependent current flow in both intact and decapsulated field-programmable gate arrays (FPGAs); and find that QDM images can determine pre-programmed IC active states with high fidelity using machine-learning classification methods.
In the 1960s, computer engineers had to address the tyranny of numbers problem in which improvements in computing and its applications required integrating an increasing number of electronic components. From the first computers powered by vacuum tubes to the billions of transistors fabricated on a single microprocessor chip today, transformational advances in integration have led to remarkable processing performance and new unforeseen applications in computing. Today, quantum scientists and engineers are facing similar integration challenges. Research labs packed with benchtop components, such as tunable lasers, tables filled with optics, and racks of control hardware, are needed to prepare, manipulate, and read out quantum states from a modest number of qubits. Analogous to electronic circuit design and fabrication nearly five decades ago, scaling quantum systems (i.e. to thousands or millions of components and quantum elements) with the required functionality, high performance, and stability will only be realized through novel design architectures and fabrication techniques that enable the chip-scale integration of electronic and quantum photonic integrated circuits (QPIC). In the next decade, with sustained research, development, and investment in the quantum photonic ecosystem (i.e. PIC-based platforms, devices and circuits, fabrication and integration processes, packaging, and testing and benchmarking), we will witness the transition from single- and few-function prototypes to the large-scale integration of multi-functional and reconfigurable QPICs that will define how information is processed, stored, transmitted, and utilized for quantum computing, communications, metrology, and sensing. This roadmap highlights the current progress in the field of integrated quantum photonics, future challenges, and advances in science and technology needed to meet these challenges.
Scaling up linear-optics quantum computing will require multi-photon gates which are compact, phase-stable, exhibit excellent quantum interference, and have success heralded by the detection of ancillary photons. We investigate implementation of the optimal known gate design which meets these requirements: the Knill controlled-Z gate, implemented in integrated laser-written waveguide arrays. We show that device performance is more sensitive to the small deviations in the coupler reflectivity, arising due to the tolerance values of the fabrication method, than phase variations in the circuit. The mode fidelity was also shown to be less sensitive to reflectivity and phase errors than process fidelity. Our best device achieves a fidelity of 0.931+/-0.001 with the ideal 4x4 unitary circuit and a process fidelity of 0.680+/-0.005 with the ideal computational-basis process.