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quant-ph2026

Approximate QCAs in one dimension using approximate algebras

Daniel Ranard, Michael Walter, Freek Witteveen

Quantum cellular automata (QCAs) are automorphisms of tensor product algebras that preserve locality, with local quantum circuits as a simple example. We study approximate QCAs, wh…

quant-ph2026

Lower bounding the MaxCut of high girth 3-regular graphs using the QAOA

Edward Farhi, Sam Gutmann, Daniel Ranard +1

We study MaxCut on 3-regular graphs of minimum girth for various 's. We obtain new lower bounds on the maximum cut achievable in such graphs by analyzing the Quantum Approxi…

quant-ph2025

The threshold for quantum-classical correspondence is

Felipe Hernández, Daniel Ranard, C. Jess Riedel

In chaotic quantum systems, an initially localized quantum state can deviate strongly from the corresponding classical phase-space distribution after the Ehrenfest time $t_{\mathrm…

quant-ph2025

Ehrenfest's theorem beyond the Ehrenfest time

Felipe Hernández, Daniel Ranard, C. Jess Riedel

In closed quantum systems, wavepackets can spread exponentially in time due to chaos, forming long-range superpositions in just seconds for ordinary macroscopic systems. A weakly c…

quant-ph2024

Learning State Preparation Circuits for Quantum Phases of Matter

Hyun-Soo Kim, Isaac H. Kim, Daniel Ranard

Many-body ground state preparation is an important subroutine used in the simulation of physical systems. In this paper, we introduce a flexible and efficient framework for obtaini…

quant-ph2024

Strategies for running the QAOA at hundreds of qubits

Brandon Augustino, Madelyn Cain, Edward Farhi +5

We explore strategies aimed at reducing the amount of computation, both quantum and classical, required to run the Quantum Approximate Optimization Algorithm (QAOA). First, followi…