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From the 1 of 6 linked papers with an AI index.

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6 papers

quant-ph2026

Online Shadow Tomography Matching the Classical Bounds

Sitan Chen, Ryan O'Donnell, Angelos Pelecanos +1

In Online Shadow Tomography, we are given copies of an unknown -dimensional quantum state , an adversary (adaptively) proposes a sequence of bounded observables $A^{(1)},\ldo…

quant-ph2026

The Keyl-Werner algorithm is not optimal for spectrum estimation

Angelos Pelecanos, Jack Spilecki, Ewin Tang +1

The paper presents a new algorithm that estimates the eigenvalues of a quantum state using fewer copies than the traditional Keyl‑Werner method, achieving constant error with O(d^2…

quant-ph2025

Mixed state tomography reduces to pure state tomography

Angelos Pelecanos, Jack Spilecki, Ewin Tang +1

A longstanding belief in quantum tomography is that estimating a mixed state is far harder than estimating a pure state. This is borne out in the mathematics, where mixed state alg…

quant-ph2025

The debiased Keyl's algorithm: a new unbiased estimator for full state tomography

Angelos Pelecanos, Jack Spilecki, John Wright

In the problem of quantum state tomography, one is given copies of an unknown rank- mixed state and asked to produce an estimator of . In…

quant-ph2025

Beating full state tomography for unentangled spectrum estimation

Angelos Pelecanos, Xinyu Tan, Ewin Tang +1

How many copies of a mixed state are needed to learn its spectrum? To date, the best known algorithms for spectrum estimation require as many copies…

cs.CR2025

On the Computational Hardness of Quantum One-Wayness

Bruno Cavalar, Eli Goldin, Matthew Gray +3

There is a large body of work studying what forms of computational hardness are needed to realize classical cryptography. In particular, one-way functions and pseudorandom generato…