Strong empiricalAlgorithmsAlgorithmAmplitude estimation
Quantum amplitude estimation
A finance- and Monte-Carlo-facing primitive that makes the oracle and error model visible.
Every quantum algorithm worth knowing about, written down the same way: what it takes, what it returns, what it costs, and who proved it.
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The defining behavior was checked exactly: a mathematical identity, a full statevector or stabilizer simulation, or an exhaustive basis-state truth table.
The design was verified by construction plus measured evidence: statistical re-execution, small-instance analytic agreement, sub-block, echo, or invariant checks. Scale-specific bugs can still survive.
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7 public entries
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A finance- and Monte-Carlo-facing primitive that makes the oracle and error model visible.
Price discretely monitored Asian options over T monitoring points, where the underlying asset is modeled by a geometric Brownian motion.
Bound the quantum-computing resources a fault-tolerant quantum computer would need to price derivatives — autocallable and Target Accrual Redemption Forward (TARF) instruments serving as the paper's benchmark use cases — at a scale offering a quantum advantage over classical pricing.
Price an option, or a portfolio of options — vanilla contracts, multi-asset contracts, and path-dependent contracts such as barrier options — on a gate-based quantum computer, in the setting where the paper takes classical Monte Carlo methods as its point of comparison.
Price rainbow options — a type of path-independent multi-asset derivative — on a quantum computer.
Evaluate risk measures of a financial position — Value at Risk and Conditional Value at Risk among them — where the classical route is a Monte Carlo simulation over sampled realisations of the uncertainty.
A linear-algebra reference that forces the catalog to show input loading, conditioning, and output observability.