S
Subir Sachdev
Researcher at Harvard University
Publications - 613
Citations - 46428
Subir Sachdev is an academic researcher from Harvard University. The author has contributed to research in topics: Quantum phase transition & Superconductivity. The author has an hindex of 96, co-authored 594 publications receiving 41100 citations. Previous affiliations of Subir Sachdev include Perimeter Institute for Theoretical Physics & University of Connecticut.
Papers
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Fermi surfaces and gauge-gravity duality
Liza Huijse,Subir Sachdev +1 more
TL;DR: In this paper, a unified overview of the zero temperature phases of compressible quantum matter is given, i.e., phases in which the expectation value of a globally conserved U(1) density varies smoothly as a function of parameters.
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Triangular antiferromagnetism on the honeycomb lattice of twisted bilayer graphene
TL;DR: In this article, the electronic band structures of states with the same symmetry as the three-sublattice planar antiferromagnetic order of the triangular lattice were presented.
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Quantum quench of the Sachdev-Ye-Kitaev model
TL;DR: In this paper, the authors describe the nonequilibrium quench dynamics of the Sachdev-Ye-Kitaev models of fermions with random all-to-all interactions and provide tractable models of the dynamics of quantum systems without quasiparticle excitations.
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Memory matrix theory of magnetotransport in strange metals
TL;DR: In this paper, the authors model strange metals as quantum liquids without quasiparticle excitations, but with slow momentum relaxation and with slow diffusive dynamics of a conserved charge and energy, and obtain general expressions for electrical, thermal and thermoelectric transport in the presence of an applied magnetic field using the memory matrix formalism.
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Sign-Problem–Free Quantum Monte Carlo of the Onset of Antiferromagnetism in Metals
TL;DR: Here, it is shown that the universal low-energy theory for the onset of antiferromagnetism in a metal can be realized in lattice models, which are free from the sign problem and hence can be simulated efficiently with QMC.