A necessary and sufficient condition for the quantum imaginary-time Mpemba effect is that it depends only on the population ratios of excited states to the ground state.
Title resolution pending
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
fields
quant-ph 5representative citing papers
Nonnormality is an intrinsically dissipative property of Lindbladian generators that controls transient growth in open quantum dynamics and increases the cost of quantum simulations.
qSHIFT achieves L-independent gate complexity and O(t^{1+r}) error scaling in quantum simulation through adaptive sampling distributions updated by solving L^r classical linear equations per round.
Randomized sparse-QSVT reduces gate counts by up to 10x for inhomogeneous many-term Hamiltonians at moderate error (around 10^{-3}), but deterministic QSVT becomes cheaper for higher precision.
A tunable parallel amplitude estimation algorithm achieves near-Heisenberg query scaling and logarithmic depth via GHZ states and quantum signal processing, with a near-optimality proof using the parallel quantum adversary method.
citing papers explorer
-
Theory of Quantum Imaginary-Time Mpemba Effect
A necessary and sufficient condition for the quantum imaginary-time Mpemba effect is that it depends only on the population ratios of excited states to the ground state.
-
Nonnormality and Dissipation in Markovian Quantum Dynamics: Implications for Quantum Simulation
Nonnormality is an intrinsically dissipative property of Lindbladian generators that controls transient growth in open quantum dynamics and increases the cost of quantum simulations.
-
qSHIFT: An Adaptive Sampling Protocol for Higher-Order Quantum Simulation
qSHIFT achieves L-independent gate complexity and O(t^{1+r}) error scaling in quantum simulation through adaptive sampling distributions updated by solving L^r classical linear equations per round.
-
When is randomization advantageous in quantum simulation?
Randomized sparse-QSVT reduces gate counts by up to 10x for inhomogeneous many-term Hamiltonians at moderate error (around 10^{-3}), but deterministic QSVT becomes cheaper for higher precision.
-
Near-Heisenberg-limited parallel amplitude estimation with logarithmic depth circuit
A tunable parallel amplitude estimation algorithm achieves near-Heisenberg query scaling and logarithmic depth via GHZ states and quantum signal processing, with a near-optimality proof using the parallel quantum adversary method.