Semiconductors: Nanostructures and applications in spintronics and quantum computation

Background. Quantum computing is a technology that has great potential to revolutionize various scientific disciplines with its extraordinary computing capabilities. Multiple fields, such as cryptography, optimization, and complex simulation, have begun to explore quantum computing applications. However, a deep understanding of how these technologies can be used effectively in cross-disciplinary informatics still needs to be improved. Purpose. This research aims to develop a theoretical framework that explains the role of quantum computing in advancing interdisciplinary informatics. The main focus is to identify potential applications and challenges faced in applying this technology in various fields and evaluate its impact on the development of science and technology. Method. This research uses a qualitative approach, a literature review, and theoretical analysis methods. Data were collected from various academic sources, including journals, books, and conferences relevant to quantum computing and interdisciplinary informatics. Analysis was conducted to identify patterns, themes, and relationships between quantum computing and cross-disciplinary applications. Results. The research results show that quantum computing has the potential to solve complex computational problems in various fields, including cryptography, optimization, and physical simulation. Quantum computing can provide more efficient and faster solutions than classical computing. However, the research also identified several significant challenges, such as the need for quantum-specific algorithms and sophisticated technological infrastructure. Conclusion. Quantum computing is essential in advancing interdisciplinary informatics by providing superior computing capabilities. The theoretical framework developed in this research can be used to further study and develop quantum computing applications in various fields. The identified challenges require special attention to ensure effective and efficient implementation of this technology.

The emerging ability to measure and control electron spins in nano-structured materials down to the level of single spins is at the heart of the research field of spintronics, with potential applications in logic and quantum computation. In current semiconductor-based logic devices, the electron spin is a quantity that is mostly neglected. The switching functionality of a conventional field-effect transistor is based on charging a channel region with electrons. For a given on/off ratio of the source-drain current, the switching requires a minimum voltage swing related to the thermal energy, which sets a lower limit on the active power consumption of the device. Such a principal limitation is not present if the spin direction of electrons is switched. This observation has triggered huge interest in spintronics as a low-power alternative for logic devices. With the example of existing spintronics device concept, the challenges for using spin switches in logic applications will be discussed. Very large spin filtering efficiencies are needed to use a spin switch as a drop-in replacement for FET-based current switches, setting demanding requirements for the processes of spin injection and detection. An alternative approach is to encode the digital information directly into the spin state and omit excess spin-to-charge conversion, which however requires the development of spin amplification to achieve gain in the spin domain. Many spintronics device concepts comprise nonmagnetic regions where non-equilibrium spin polarization is switched by electrical fields. There, the spins have to be processed within the respective spin lifetime. We will discuss how spinorbit interaction limits the spin lifetime but at the same time is needed for electrical spin switching. Experimental results based on time-resolved magneto-optical Kerr rotation will be shown that demonstrate fast switching of spins in GaAs-based semiconductor quantum structures with specially engineered spin-orbit interaction where the influence on the spin lifetime is lifted.

We show how realistic charge manipulation and measurement techniques, combined with the exchange interaction, allow for the robust generation and purification of four-particle spin entangled states in electrically controlled semiconductor quantum dots. The generated states are immunized to the dominant sources of noise via a dynamical decoherence-free subspace; all additional errors are corrected by a purification protocol. This approach may find application in quantum computation, communication, and metrology.

Laser cooling and trapping1,2, and magneto-optical trapping methods in particular2, have enabled groundbreaking advances in science, including Bose-Einstein condensation3-5, quantum computation with neutral atoms6,7 and high-precision optical clocks8. Recently, magneto-optical traps (MOTs) of diatomic molecules have been demonstrated9-12, providing access to research in quantum simulation13 and searches for physics beyond the standard model14. Compared with diatomic molecules, polyatomic molecules have distinct rotational and vibrational degrees of freedom that promise a variety of transformational possibilities. For example, ultracold polyatomic molecules would be uniquely suited to applications in quantum computation and simulation15-17, ultracold collisions18, quantum chemistry19 and beyond-the-standard-model searches20,21. However, the complexity of these molecules has so far precluded the realization of MOTs for polyatomic species. Here we demonstrate magneto-optical trapping of a polyatomic molecule, calcium monohydroxide (CaOH). After trapping, the molecules are laser cooled in a blue-detuned optical molasses to a temperature of 110 μK, which is below the Doppler cooling limit. The temperatures and densities achieved here make CaOH a viable candidate for a wide variety of quantum science applications, including quantum simulation and computation using optical tweezer arrays15,17,22,23. This work also suggests that laser cooling and magneto-optical trapping of many other polyatomic species24-27 will be both feasible and practical.

With the explosion of big data, higher requirements for computational efficiency have emerged. Compared with classical computing, quantum computing possesses quantum parallelism due to the unique nature of quantum systems. It has been found that many classical algorithms can be accelerated using quantum computing. In addition to factorizing a large integer, quantum computers can be used for data processing and analysis. In recent years, two frontiers, i.e., big data and quantum computing have begun to merge. Though practical quantum computers have not yet been built, theoretical studies have made some important progress. In this review, we introduce the basic principles of quantum computing. As a representative example, we describe the Grover search algorithm and its important generalizations. Quantum machine learning is the entry point for the integration of big data with quantum computation. We review in detail, the applications of quantum computation in data mining, the main application of machine learning. Other aspects of quantum computing in big data are also briefly summarized.

Three-dimensional topological insulators are characterized by insulating bulk state and metallic surface state involving relativistic Dirac fermions which are responsible for exotic quantum phenomena and potential applications in spintronics and quantum computations. It is essential to understand how the Dirac fermions interact with other electrons, phonons and disorders. Here we report super-high resolution angle-resolved photoemission studies on the Dirac fermion dynamics in the prototypical Bi2(Te,Se)3 topological insulators. We have directly revealed signatures of the electron-phonon coupling and found that the electron-disorder interaction dominates the scattering process. The Dirac fermion dynamics in Bi2(Te3−xSex) topological insulators can be tuned by varying the composition, x, or by controlling the charge carriers. Our findings provide crucial information in understanding and engineering the electron dynamics of the Dirac fermions for fundamental studies and potential applications.

Weyl Semimetals have substantial applications in spintronics, quantum computation, and electronic industry. Therefore, to get a physical insight behind the electronic applications of these Weyl semimetals, the electronic band structure, total as well as partial phonon density of states, Fermi surfaces and charge density contours related to Zirconium based Weyl semimetals ZrX (X = S, Se and Te) are investigated and discussed in the present report using generalized gradient approximations by employing density functional theory. From the calculated values of bulk modulus Bo and its derivative with respect to change in pressure values Bo/, it is found that ZrS possesses the highest value of Bo and Bo/ among all. This confirms that ZrS has least compressibility. The Fermi surfaces of ZrX are composed of two bands traversing along with M-L directions of the Brillouin zone. The bonding characteristics are determined by using the electronic charge density contours in the (110) plane of crystallography. The present calculation suggests the ionic and polar-covalent bonding in the WSMs, which is found to be in consistent with the electro-negativity difference values.

Spin-valley properties in two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDCs) has attracted significant interest due to the possible applications in quantum computing. Spin-valley properties can be exploited in TMDC quantum dot (QD) with well-resolved energy levels. This requires smaller QDs, especially in material systems with heavy carrier effective mass e.g. TMDCs and silicon. Device architectures employed for TMDC QDs so far have difficulty achieving smaller QDs. Therefore, an alternative approach in the device architecture is needed. Here, we propose a multilayer device architecture to achieve a gate-defined QD in TMDC with a relatively large energy splitting on the QD. We provide a range of device dimensions and dielectric thicknesses and its correlation with the QD energy splitting. The device architecture is modeled realistically. Moreover, we show that all the device parameters used in modeling are experimentally achievable. These studies lay the foundation for future work toward spin-valley qubits in TMDCs. The successful implementation of these device architectures will drive the technological development of 2D materials-based quantum technologies.

The creation of specified quantum states is important for most, if not all, applications in quantum computation and communication. The quality of the state preparation is therefore an essential ingredient in any assessment of a quantum-state gun. We show that the fidelity, under the standard definitions is not sufficient to assess quantum sources, and we propose a new measure of suitability that necessarily depends on the application for the source. We consider the performance of single-photon guns in the context of quantum key distribution (QKD) and linear optical quantum computation. Single-photon sources for QKD need radically different properties than sources for quantum computing. Furthermore, the suitability for single-photon guns is discussed explicitly in terms of experimentally accessible criteria.

Majorana zero modes (MZMs) at the boundary of topological superconductors (TSC) have garnered significant attention for their application in quantum computation. In this study, we demonstrate that in heterostructures composed of the one-dimensional (1D) chiral nanowire and a superconductor, structural chirality could induce the spin-triplet-polarized MZMs. Interestingly, the opposite spin-polarized MZMs are robustly localized at the end of nanowire, whose direction depends on the chirality. Furthermore, this spin-triplet polarization gives rise to chirality-dependent spin-polarized local Andreev reflection (LAR) processes at the TSC/normal metal interface, providing a mechanism for detecting MZMs in TSC-based devices. Finally, we also demonstrate that the chirality-dependent spin-polarized MZMs and LAR processes could be realized in the experimentally accessible 1D helical ${\mathrm{NbSe}}_{\text{3}}$ nanowire. Thus, our findings offer insights into the realization and manipulation of MZMs in 1D chiral systems, with implications for spintronic applications in TSC-based devices.

In recent years, zinc oxide (ZnO) quantum dots (QDs) have gained much attention due to their quantum and piezoelectric properties, which make them viable candidates for optoelectronic applications and nano-sensing devices. The piezoelectric properties of ZnO QDs are intimately linked to their optoelectronic behavior in response to mechanical stress and applied external forces. First-principle calculations of the electronic properties of the QDs have been performed using density functional theory (DFT) to compute their electronic structure, density of states (DOS), charge density, phonon behavior, and the photoluminescence properties of the material. Moreover, the size-dependent quantum confinement effect can be seen through the discrete energy levels in the band structure, which results in defined peaks in the DOS and blue shift in the photoluminescence. The bandgap energy of ZnO QDs determines the conductivity of the material and is dependent on the size of the QDs. This property in turn allows for tunability of the electronic properties of the QDs as a function of their size and is thereby appropriate for optoelectronic, photonic, and sensing applications. The nano-scale sizes and quantum properties of ZnO QD qubits also make them suitable for applications in quantum computing and data storage.

A Busy March Meeting Is Brewing in Seattle

Exotic particles called Majorana fermions have potential applications in quantum computing, but their existence has yet to be definitively confirmed. Two groups have now glimpsed these particles. Exotic particles called Majorana fermions have potential applications in quantum computing, but their existence has yet to be definitively confirmed. Two groups have now glimpsed these particles.

Quantum computing (QC) is not a futuristic notion in agriculture, though its full potential has yet to be realized. QC is an emerging field at the intersection of physics and computer science that holds immense potential to revolutionize various sectors, including agriculture production and artificial intelligence (AI) modeling. While QC is still in the early stages of development and practical applications within agriculture are not yet widespread, researchers are actively exploring its potential benefits in various agricultural domains, including crop optimization, livestock breeding, and environmental monitoring. QC harnesses the principles of quantum mechanics to perform computations using quantum bits or qubits, which can exist in multiple states simultaneously. Unlike classical computers, which rely on binary bits representing 0 or 1, quantum computers exploit phenomena such as superposition and entanglement to process information in parallel, potentially offering exponential speedup for certain types of problems. In agriculture production, particularly in animal science, QC offers promising avenues for optimizing processes and enhancing productivity. Quantum algorithms can analyze vast amounts of genomic data to improve breeding programs, leading to the development of more resilient and productive livestock breeds. Furthermore, QC can facilitate precision farming techniques by modeling complex environmental factors and animal behavior to optimize feeding strategies, disease management, and overall farm management practices. Moreover, QC can significantly benefit AI modeling by accelerating computations and enabling more efficient training of AI models. Quantum algorithms can enhance the performance of AI algorithms in various tasks, including pattern recognition, natural language processing, and predictive analytics. By leveraging quantum-enhanced optimization algorithms, AI models can achieve better convergence and accuracy, leading to more effective decision-making and problem-solving capabilities. While hybrid intelligent models also represent a novel frontier in agriculture, QC has the potential to expedite the merging of mechanistic and AI modeling paradigms, facilitating a more holistic understanding of complex systems in agriculture and beyond. By integrating mechanistic models, which describe the underlying physical processes, with AI models, which learn patterns from data, quantum computing can enable comprehensive simulations and predictions of agricultural systems. This fusion of modeling paradigms can lead to more accurate and robust predictions of crop yields, livestock performance, and environmental impacts, facilitating informed decision-making for farmers and policymakers. The application of QC in agriculture, however, requires interdisciplinary collaborations between physicists, computer scientists, agronomists/animal scientists, and AI researchers. These collaborations can drive the development of quantum algorithms tailored to agricultural applications, the integration of quantum-enhanced AI techniques into existing modeling frameworks, and the deployment of QC resources in real-world agricultural systems. Ultimately, harnessing the power of QC holds the potential to revolutionize agriculture production practices, including regenerative agriculture, and advance AI modeling capabilities, paving the way for a more sustainable and efficient agricultural industry.

Multiple‐qubit logic gates, as an essential part of quantum logic gates, have wide practical application in quantum computation. Here, a scheme to directly construct a multiple‐qubit logic gate , in which k control atoms apply an universal operation U on each of m target qubits in the Rydberg atom system is proposed. The scheme, based on Rydberg blockade and geometric quantum operations as well as optimized control theory, can greatly reduce the qubit number and the operation steps, improving the speed and robustness of the gating compared to the conventional multiple‐qubit gates consisting of single‐ and two‐qubit gates. Taking the C2U2 gate as an example, the performance of the proposal is numerically evaluated in terms of the fidelity of the quantum gate as well as the robustness against the static systematic errors and spontaneous emission. This work may provide a significative reference for constructing universal multiple‐qubit logic gates in future Rydberg atom experiments.