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From the 2 of 16 linked papers with an AI index.

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20242026
most citedPhase estimation with partially randomized time evolution

2 citations · 3 across the 7 of their papers we have counts for

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quant-ph2026

Optimal Quantum Algorithm for Ground-State Energy Estimation with a Guiding State

Stacey Jeffery, Freek Witteveen

In the problem of ground-state energy estimation, one aims to estimate the smallest eigenvalue of a Hamiltonian, often given a guiding state, with some promised overlap with th…

quant-ph20261 cited

phase2: Full-State Vector Simulation of Quantum Time Evolution at Scale

Marek Miller, Jakob Günther, Freek Witteveen +5

phase2 is a full-state-vector quantum simulator that efficiently handles many-qubit Pauli rotation circuits on distributed CPU/GPU clusters, achieving large speedups and scaling to…

quant-ph2026

Optimal tomography of bosonic and fermionic Gaussian states

Senrui Chen, Marco Fanizza, Filippo Girardi +4

The paper determines the exact sample complexity for learning bosonic and fermionic Gaussian quantum states, showing that a number of copies scaling quadratically with the number o…

quant-ph20262 cited

Phase estimation with partially randomized time evolution

Jakob Günther, Freek Witteveen, Alexander Schmidhuber +3

Quantum phase estimation combined with Hamiltonian simulation is the most promising algorithmic framework to computing ground state energies on quantum computers. Its main computat…

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

Randomized truncation of quantum states

Aram W. Harrow, Angus Lowe, Freek Witteveen

A fundamental task in quantum information is to approximate a pure quantum state in terms of sparse states or, for a bipartite system, states of bounded Schmidt rank. The optimal d…