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Krishnanand Mallayya

Showing results (1-10 of 6) with videos related to

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Physical Review. E|April 19, 2017
Numerical linked cluster expansions for quantum quenches in one-dimensional latticesKrishnanand Mallayya, Marcos Rigol
Physical Review Letters|January 11, 2020
Heating Rates in Periodically Driven Strongly Interacting Quantum Many-Body SystemsKrishnanand Mallayya, Marcos Rigol
Physical Review Letters|March 16, 2018
Quantum Quenches and Relaxation Dynamics in the Thermodynamic LimitKrishnanand Mallayya, Marcos Rigol
Physical Review. E|January 23, 2020
Entanglement and matrix elements of observables in interacting integrable systemsTyler LeBlond, Krishnanand Mallayya, Lev Vidmar, et al.
Proceedings of the National Academy of Sciences of the United States of America|August 6, 2024
Real-space visualization of a defect-mediated charge density wave transitionJames L Hart, Haining Pan, Saif Siddique, et al.
Proceedings of the National Academy of Sciences of the United States of America|June 9, 2022
Harnessing interpretable and unsupervised machine learning to address big data from modern X-ray diffractionJordan Venderley, Krishnanand Mallayya, Michael Matty, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
Physical Review. E|April 19, 2017
Numerical linked cluster expansions for quantum quenches in one-dimensional latticesKrishnanand Mallayya, Marcos Rigol
Physical Review Letters|January 11, 2020
Heating Rates in Periodically Driven Strongly Interacting Quantum Many-Body SystemsKrishnanand Mallayya, Marcos Rigol
Physical Review Letters|March 16, 2018
Quantum Quenches and Relaxation Dynamics in the Thermodynamic LimitKrishnanand Mallayya, Marcos Rigol
Physical Review. E|January 23, 2020
Entanglement and matrix elements of observables in interacting integrable systemsTyler LeBlond, Krishnanand Mallayya, Lev Vidmar, et al.
Proceedings of the National Academy of Sciences of the United States of America|August 6, 2024
Real-space visualization of a defect-mediated charge density wave transitionJames L Hart, Haining Pan, Saif Siddique, et al.
Proceedings of the National Academy of Sciences of the United States of America|June 9, 2022
Harnessing interpretable and unsupervised machine learning to address big data from modern X-ray diffractionJordan Venderley, Krishnanand Mallayya, Michael Matty, et al.
Pageof 1