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20002026
most citedQuantum attacks on Bitcoin, and how to protect against them

225 citations

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67 papers · 1 filter

quant-ph2025

Quantum Agents for Algorithmic Discovery

Iordanis Kerenidis, El-Amine Cherrat

We introduce quantum agents trained by episodic, reward-based reinforcement learning to autonomously rediscover several seminal quantum algorithms and protocols. In particular, our…

quant-ph2025

Self-concordant Schrödinger operators: spectral gaps and optimization without condition numbers

Sander Gribling, Simon Apers, Harold Nieuwboer +1

Spectral gaps play a fundamental role in many areas of mathematics, computer science, and physics. In quantum mechanics, the spectral gap of Schrödinger operators has a long histor…

quant-ph2024

On the dynamical Lie algebras of quantum approximate optimization algorithms

Jonathan Allcock, Miklos Santha, Pei Yuan +1

Dynamical Lie algebras (DLAs) have emerged as a valuable tool in the study of parameterized quantum circuits, helping to characterize both their expressiveness and trainability. In…

quant-ph2024★ 2 cited

Training-efficient density quantum machine learning

Brian Coyle, Snehal Raj, Natansh Mathur +4

Quantum machine learning (QML) requires powerful, flexible and efficiently trainable models to be successful in solving challenging problems. We introduce density quantum neural ne…

quant-ph2024

Quantum option pricing via the Karhunen-Loève expansion

Anupam Prakash, Yue Sun, Shouvanik Chakrabarti +8

We consider the problem of pricing discretely monitored Asian options over monitoring points where the underlying asset is modeled by a geometric Brownian motion. We provide tw…

quant-ph2024

Quantum walks, the discrete wave equation and Chebyshev polynomials

Simon Apers, Laurent Miclo

A quantum walk is the quantum analogue of a random walk. While it is relatively well understood how quantum walks can speed up random walk hitting times, it is a long-standing open…