Tameem Albash, Ph.D.
Affiliations: | 2010 | Physics | University of Southern California, Los Angeles, CA, United States |
Area:
glutamate receptors, LTP, neurodegeneration, calpainGoogle:
"Tameem Albash"Mean distance: 17.9 (cluster 6) | S | N | B | C | P |
Parents
Sign in to add mentor| Clifford R. Johnson | grad student | 2010 | USC | |
| (Phenomenological AdS/CFT: Applications to condensed matter.) | ||||
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Publications
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| Albash T. (2020) Validating a two-qubit nonstoquastic Hamiltonian in quantum annealing Physical Review A. 101 |
| Albash T. (2019) Role of nonstoquastic catalysts in quantum adiabatic optimization Physical Review A. 99 |
| Slutskii M, Albash T, Barash L, et al. (2019) Analog nature of quantum adiabatic unstructured search New Journal of Physics. 21: 113025 |
| Mishra A, Albash T, Lidar DA. (2018) Finite temperature quantum annealing solving exponentially small gap problem with non-monotonic success probability. Nature Communications. 9: 2917 |
| Novikov S, Hinkey R, Disseler S, et al. (2018) Exploring More-Coherent Quantum Annealing Arxiv: Quantum Physics. 1-7 |
| Albash T, Lidar DA. (2018) Adiabatic quantum computation Reviews of Modern Physics. 90 |
| Albash T, Lidar DA. (2018) Demonstration of a Scaling Advantage for a Quantum Annealer over Simulated Annealing Physical Review X. 8 |
| Yip KW, Albash T, Lidar DA. (2018) Quantum trajectories for time-dependent adiabatic master equations Physical Review A. 97 |
| Albash T, Wagenbreth G, Hen I. (2017) Off-diagonal expansion quantum Monte Carlo. Physical Review. E. 96: 063309 |
| Albash T, Martin-Mayor V, Hen I. (2017) Temperature Scaling Law for Quantum Annealing Optimizers. Physical Review Letters. 119: 110502 |