Bounds for the adiabatic approximation with applications to quantum computation

By S. Jansen, Mary Beth Ruskai, R. Seiler. 2006

410 citations recorded by the source corpus.

We present straightforward proofs of estimates used in the adiabatic approximation. The gap dependence is analyzed explicitly. We apply the result to interpolating Hamiltonians of interest in quantum computing.

Subfields: Artificial Intelligence, Mathematical Physics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/3a4e9faf74d27a715258e475be0606f1f3454325

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Tameem Albash
2. Liang Jiang
3. Victor V. Albert
4. Daniel A. Lidar
5. M. Fraas
6. Barry Bradlyn
7. Ivan H. Deutsch
8. Steven M. Girvin

In Mathematical Physics

1. Daniel A. Lidar
2. Tameem Albash
3. M. Fraas

In Statistical and Nonlinear Physics

1. Daniel A. Lidar
2. Victor V. Albert
3. Tameem Albash
4. V. Hubeny

Citations in the corpus

• Adiabatic Quantum Computing (2016, methodology): “Jansen, Ruskai, and Seiler (JRS) proved several versions of the AT that build upon these techniques (Jansen et al., 2007), and that rigorously establish the gap dependence of tf , without any strong assumptions on the smoothness of H(s).”
• Geometry and Response of Lindbladians (2015, background): “In Hamiltonian systems, the adiabatic path length appears in bounds on corrections to adiabatic evolution ([176], Thm.”
• Decoherence in adiabatic quantum computation (2015, background): “[49] Sabine Jansen, Mary-Beth Ruskai, and Ruedi Seiler, “Bounds for the adiabatic approximation with applications to quantum computation,” J.”