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Bulletin of the American Physical Society

Entangled Neutron Beams: A possible new avenue to exploring Quantum Materials

David V. Baxter, C. Broholm, Abu Ashik Irfan, Stephen J. Kuhn, Shufan Lu, Gerardo Ortíz, R. Pynn, Jiazhou Shen, William Michael Snow

Published Mar 2, 2020• 0 citations
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Neutron interferometry with its ability to encode and extract information provides a test \nbed for quantum mechanics and precise measurement of physical quantities of significant \nimportance in physics. However, this significant key investigative technique is weakened \nby its very fragile nature; neutron interferometry has proven to be highly sensitive to \nenvironmental noise. \n \nOnce brought to its optimal state, the use of neutron interferometry enabled with \nquantum information, represents a milestone. Indeed a realization of high-quality neutron \ninterferometry could pave a way to probe materials research such as probing properties \nwater in proteins and topological materials. Thus understanding and solving the sensitivity \nof neutron interferometers to noise is a key step toward possible applications. This is the \ncore of the work done in this Thesis. \n \nWe incorporated two theoretical techniques developed for quantum information sciences \ninto the construction of a new polarized neutron interferometry beam line: The technique \nof quantum error correction and the technique of open quantum system. One focus of this \nwork is to report on the design, the construction as well as the characteristic features of \nthis beamline. \n \nThis thesis involves experimental data, showing how the neutron beam intensity at the \nexit of a three-blade neutron interferometer can be controlled by the interferometer blades \nthickness. Secondly, is also presents an alternative and simplified quantum information \napproach to dynamical diffraction, based on repeated application of a coherent beam- \nsplitting unitary at coarse-grained lattice sites. Demanding translational invariance added \nto a computationally tractable number of sites in the coarse-graining reproduced many \nresults typical of standard dynamical diffraction theory and experiments. Building on that, \na proposal for a new five-blade neutron interferometer is presented and its robustness to \nnoise, resulting from dynamical diffraction together with low-frequency external mechanical \nvibration is discussed. \n \nSteps ahead in our work, neutron interferometry may be improved as well as adapted to \nmore applications by incorporating the spin and orbital degrees of freedom to a path-based \nivinterferometer. In this concern, we propose a method to prepare the spin-orbit state by \npassing a polarized neutron beam through a quadrupole magnetic field. Initially designed \nfor a beam the size of a coherent length, we extend this method to work for spatially \ndisplaced beams by using linear magnetic gradients.

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Neutron interferometry with its ability to encode and extract information provides a test \nbed for quantum mechanics and precise measurement of physical quantities of significant \nimportance in physics. However, this significant key investigative technique is weakened \nby its very fragile nature; neutron interferometry has proven to be highly sensitive to \nenvironmental noise. \n \nOnce brought to its optimal state, the use of neutron interferometry enabled with \nquantum information, represents a milestone. Indeed a realization of high-quality neutron \ninterferometry could pave a way to probe materials research such as probing properties \nwater in proteins and topological materials. Thus understanding and solving the sensitivity \nof neutron interferometers to noise is a key step toward possible applications. This is the \ncore of the work done in this Thesis. \n \nWe incorporated two theoretical techniques developed for quantum information sciences \ninto the construction of a new polarized neutron interferometry beam line: The technique \nof quantum error correction and the technique of open quantum system. One focus of this \nwork is to report on the design, the construction as well as the characteristic features of \nthis beamline. \n \nThis thesis involves experimental data, showing how the neutron beam intensity at the \nexit of a three-blade neutron interferometer can be controlled by the interferometer blades \nthickness. Secondly, is also presents an alternative and simplified quantum information \napproach to dynamical diffraction, based on repeated application of a coherent beam- \nsplitting unitary at coarse-grained lattice sites. Demanding translational invariance added \nto a computationally tractable number of sites in the coarse-graining reproduced many \nresults typical of standard dynamical diffraction theory and experiments. Building on that, \na proposal for a new five-blade neutron interferometer is presented and its robustness to \nnoise, resulting from dynamical diffraction together with low-frequency external mechanical \nvibration is discussed. \n \nSteps ahead in our work, neutron interferometry may be improved as well as adapted to \nmore applications by incorporating the spin and orbital degrees of freedom to a path-based \nivinterferometer. In this concern, we propose a method to prepare the spin-orbit state by \npassing a polarized neutron beam through a quadrupole magnetic field. Initially designed \nfor a beam the size of a coherent length, we extend this method to work for spatially \ndisplaced beams by using linear magnetic gradients.
Quantum Machine Learning (QML) represents a paradigm shift in computational science, leveraging quantum mechanics to unlock new possibilities across diverse fields. This paper explores the development of a novel geometric expansion technique, utilizing quantum superposition and entanglement to dramatically enhance the capabilities of quantum computation. We propose a framework where geometric calculations are intrinsically linked to quantum algorithms, allowing for the simulation of complex geometric structures and quantum systems with unprecedented efficiency. The core claim is that this geometric expansion can overcome the limitations of classical computation, opening avenues for advanced modeling and analysis in areas like materials science, drug discovery, and fundamental physics. This work details the underlying mechanisms, explores the potential applications, and provides a preliminary assessment of the technological feasibility of this approach.