Pub Date : 2025-02-18DOI: 10.22331/q-2025-02-18-1635
Lucas Marti, Refik Mansuroglu, Michael J. Hartmann
We present a cooling algorithm for ground state preparation of fermionic Hamiltonians. Our algorithm makes use of the Hamiltonian simulation of the considered system coupled to an ancillary fridge, which is regularly reset to its known ground state. We derive suitable interaction Hamiltonians that originate from ladder operators of the free theory and initiate resonant gaps between system and fridge. We further propose a spectroscopic scan to find the relevant eigenenergies of the system using energy measurements on the fridge. With these insights, we design a ground state cooling algorithm for fermionic systems that is efficient, i.e. its runtime is polynomial in the system size, as long as the initial state is prepared in a low-energy sector of polynomial size. We achieve the latter via a pseudo-adiabatic sweep from a parameter regime whose ground state can be easily prepared. We estimate that our algorithm has a polynomial runtime for systems where the spectral gap decreases at most polynomially in system size, and is faster than the adiabatic algorithm for a large range of settings. We generalize the algorithm to prepare thermal states and demonstrate our findings on the Fermi-Hubbard model.
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Pub Date : 2025-02-18DOI: 10.22331/q-2025-02-18-1636
Niels Kornerup, Jonathan Sadun, David Soloveichik
Pebble games are popular models for analyzing time-space trade-offs. In particular, reversible pebble game strategies are frequently applied in quantum algorithms like Grover's search to efficiently simulate classical computation on inputs in superposition, as unitary operations are fundamentally reversible. However, the reversible pebble game cannot harness the additional computational power granted by intermediate measurements, which are irreversible. The spooky pebble game, which models interleaved Hadamard basis measurements and adaptive phase corrections, reduces the number of qubits beyond what purely reversible approaches can achieve. While the spooky pebble game does not reduce the total space (bits plus qubits) complexity of the simulation, it reduces the amount of space that must be stored in qubits. We prove asymptotically tight trade-offs for the spooky pebble game on a line with any pebble bound. This in turn gives a tight time-qubit tradeoff for simulating arbitrary classical sequential computation when using the spooky pebble game. For example, for all $epsilon in (0,1]$, any classical computation requiring time $T$ and space $S$ can be implemented on a quantum computer using only $O(T/ epsilon)$ gates and $O(T^{epsilon}S^{1-epsilon})$ qubits. This improves on the best known bound for the reversible pebble game with that number of qubits, which uses $O(2^{1/epsilon} T)$ gates. For smaller space bounds, we show that the spooky pebble game can simulate arbitrary computation with $O(T^{1+epsilon} S^{-epsilon}/epsilon)$ gates and $O(S / epsilon)$ qubits whereas any simulation via the reversible pebble game requires $Omega(S cdot (1+log(T/S)))$ qubits.