47th Annual IEEE Symposium on, pages 143–152.
10.1137/070682575. URL https://arxiv.org/abs/1811.04852. The movielens datasets: History and context. https://doi.org/10.1038/ncomms5213, [28] Dénes Petz.
We conduct a theoretical analysis aimed at identifying their computational bottlenecks, then implement and benchmark the algorithms on a variety of problems, including applications to portfolio optimization and movie recommendations. https://doi.org/10.1145/2827872, [14] Aram W Harrow, Avinatan Hassidim, and Seth Lloyd. arXiv preprint arXiv:1811.03147, 2018. arXiv:1811.03147, [17] Tyson Jones, Suguru Endo, Sam McArdle, Xiao Yuan, and Simon C Benjamin.
Join to Connect. 10.1016/j.physrep.2017.07.001. https://doi.org/10.1038/srep00243, [5] Giuseppe Carleo, Federico Becca, Laurent Sanchez-Palencia, Sandro Sorella, and Michele Fabrizio. https://github.com/XanaduAI/pennylane, [36] Xiao Yuan, Suguru Endo, Qi Zhao, Ying Li, and Simon C Benjamin. In Foundations of Computer Science (FOCS), 2012 IEEE 53rd Annual Symposium on, pages 361–369. Louisiana State University. The Journal of Finance, 7 (1): 77–91, 1952. Low-depth gradient measurements can improve convergence in variational hybrid quantum-classical algorithms.
arXiv:1901.03254, [6] AV Abs da Cruz, Marley Maria Bernardes Rebuzzi Vellasco, and Marco Aurélio Cavalcanti Pacheco. 10.1137/090771806. Experimental Optics and Photonics, Experiment and theory of quantum imaging, metrology, and emulation of quantum gravity, Quantum sensing, quantum control, and optical communication using OAM, Quantum optics, the interface of quantum mechanics and general relativity, Modeling the environment noise on an NV center qubit using coherent population trapping, Entangling light via a quantum nanomechanical oscillator, Quantum many-body systems, interface of general relativity and quantum optics, Quantum information: communication protocols and thermodynamic aspects, Quantum cryptography, quantum networks, quantum computation, and open quantum systems, Quantum computing, quantum machine learning, Quantum sensors with machine learning using NV diamonds, Quantum optics, quantum information, and quantum computation, Quantum computing, quantum information theory, and quantum information with continuous variables, Quantum clock synchronization with networks of satellites, Design of network of entanglement-distributing satellites, Quantum teleportation, quantum networks, quantum computation and information, Quantum optimization, quantum control theory, quantum information, Mathematics (especially functional analysis) and applications to quantum information theory, Graduated 2020 - Postdoctoral researcher at Brookhaven National Laboratory, Graduated 2020 - Postdoctoral researcher at University of Maryland, Graduated 2020 - Postdoctoral researcher at University of Toronto, Graduated 2020 - Postdoctoral researcher at University of Waterloo, Graduated 2019 - Postdoctoral researcher at Argonne National Laboratory, Graduated 2019 - Currently at Stennis Space Center, Graduated 2019 - Postdoctoral fellow at LSU, Graduated 2018 - Postdoctoral fellow at Université libre de Bruxelles, Graduated 2018, Quantum Physicist - Air Force Research Lab, Graduated 2018 - Postdoctoral fellow at Applied Research Laboratories, Graduated 2017 - Research scientist at Xanadu, Former visiting PhD student working on quantum cryptography, quantum information theory, and quantum computation, Graduated 2016 - Postdoctoral research at National Institute for Standards and Technology, Graduated 2016 - Postdoc at Harvard University, founding scientist at Zapata Computing, Graduated 2016 - Research Associate at Virginia Tech, Graduated 2016 - Postdoctoral researcher at Harish-Chandra Research Institute, Graduated 2016 - Global Credit Quant Analyst, Graduated 2015 - Faculty at Family Christian Academy, Graduated 2015 - Postdoctoral researcher at University of Arizona, Graduated 2014 - Research Engineer-Quantum Algorithms at Ford Motor Company Research, Graduated 2014 - Seismic Imager at CGG Corporation, Graduated 2012 - Quantitative Analyst at Chatham Financial, Graduated 2010 (Distinguished Dissertation) - Assistant Professor, University of Dayton, Graduated 2009 - Director - Data science and Analytics at Omnitracs, Graduated 2009 - CEO and Founder at Deep Science AI, Graduated 2009 - Assistant Professor, Tulane University, Graduated 2008 - Associate Professor, Boise State University, Research Engineer-Quantum Algorithms at Ford Motor Company Research, Ball Family Distinguished Professor of Physics, Assistant Professor of Electrical Engineering, Postdoctoral researcher at Harish-Chandra Research Institute, Postdoctoral researcher at University of Arizona, LSU Center for Computation and Technology, Institute of Electrical and Electronics Engineers. https://doi.org/10.1016/j.acha.2007.12.002. 10.22331/q-2019-10-07-191. I love to listen, watch, read and—quite recently—write stories. Geometric Phases In Physics. Noise Resilience of Variational Quantum Compiling [New Journal of Physics] Kunal Sharma, SK, Marco Cerezo, Patrick J. Coles Contributed talk at QuILT 2019. npj Quantum Information, 5 (1): 1–6, 2019.
of Physics and Astronomy, Center for Computation and Technology, Louisiana State University, Postdoctoral Research Associate, Los Alamos National Laboratory, National Institute of Information and Communications Technology, Hearne Institute for Theoretical Physics, Physics and Astronomy, Louisiana State University, Theoretical Division, Los Alamos National Laboratory, Professor of Physics Division, Harish-Chandra Research Institute, Allahabad, India, Postdoctoral Associate, Los Alamos National Laboratory, Ph.D MIT'19, Post-Doctoral Fellow, University of Gdansk, University of Electro-Communications (Japan), Research Scientist, Information Sciences CCS-3, Los Alamos National Laboratory, Bounding the energy-constrained quantum and private capacities of phase-insensitive bosonic Gaussian channels, Noise resilience of variational quantum compiling, Trainability of Dissipative Perceptron-Based Quantum Neural Networks, Noise-induced barren plateaus in variational quantum algorithms, Information-theoretic aspects of the generalized amplitude-damping channel, Distribution of Bell-inequality violation versus multiparty-quantum-correlation measures, Entanglement-assisted private communication over quantum broadcast channels, Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets, Characterizing the performance of continuous-variable Gaussian quantum gates, Error mitigation on a near-term quantum photonic device.
[24] Srikar Kasi and Kyle Jamieson, "Towards Quantum Belief Propagation for LDPC Decoding in Wireless Networks", arXiv:2007.11069.
Nature Communications, 5: 4213, 2014. We study the practical performance of quantum-inspired algorithms for recommendation systems and linear systems of equations. Overall, our results indicate that quantum-inspired algorithms can perform well in practice provided that stringent conditions are met: low rank, low condition number, and very large dimension of the input matrix. -K. Wu, W. -G. Zhang, X. Wang, H. -L. Zhang, L. He, X. Practical optimization for hybrid quantum-classical algorithms. Quantum algorithm for linear systems of equations. 10.1038/nphys3029. Louisiana State University. [23] Viraj Kulkarni, Milind Kulkarni, and Aniruddha Pant, "Quantum Computing Methods for Supervised Learning", arXiv:2006.12025. Beating the random assignment on constraint satisfaction problems of bounded degree. 10.1137/S0097539704442696. IEEE transactions on evolutionary computation, 6 (6): 580–593, 2002. Journal of the ACM (JACM), 51 (6): 1025–1041, 2004. Fast monte carlo algorithms for matrices ii: Computing a low-rank approximation to a matrix. The optimization dynamics is interpreted as moving in the steepest descent direction with respect to the Quantum Information Geometry, corresponding to the real part of the Quantum Geometric Tensor (QGT), also known as the Fubini-Study metric tensor. 10.1109/TEVC.2002.804320. Quantum, 2: 79, 2018. In Advances in Neural Information Processing Systems, pages 2422–2430, 2015. arXiv preprint arXiv:1506.02617. arXiv:1506.02617, [27] Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J Love, Alán Aspuru-Guzik, and Jeremy L O'Brien. The Journal of Chemical Physics, 127 (1): 014105, 2007. © Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften. 10.1145/3219819.3220098.
arXiv:1505.03424, 2015. [12] Chen Ding, Tian-Yi Bao, and He-Liang Huang, "Quantum-Inspired Support Vector Machine", arXiv:1906.08902.
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