activity
20242026
most citedA Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond

8 citations · 8 across the 2 of their papers we have counts for

collaborators

6 papers

quant-ph2026

Gaussian Boson Sampling for Asset Clustering in Statistical Arbitrage Portfolios

Dayne Marcus Lopena, Daniel Buguks, Zhenghao Li +7

Gaussian Boson Sampling (GBS) provides a native photonic quantum heuristic for sampling dense subgraphs from adjacency matrices, offering a scalable physical approach to combinator…

quant-ph20268 cited

A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond

Philip Intallura, Georgios Korpas, Sudeepto Chakraborty +4

Monte Carlo sampling is a powerful toolbox of algorithmic techniques widely used for a number of applications wherein some noisy quantity, or summary statistic thereof, is sought t…

quant-ph2025

Enhanced fill probability estimates in institutional algorithmic bond trading using statistical learning algorithms with quantum computers

Axel Ciceri, Austin Cottrell, Joshua Freeland +13

The estimation of fill probabilities for trade orders represents a key ingredient in the optimization of algorithmic trading strategies. It is bound by the complex dynamics of fina…

physics.comp-ph2025

Effects of the entropy source on Monte Carlo simulations

Anton Lebedev, Annika Möslein, Olha I. Yaman +2

In this paper we show how different sources of random numbers influence the outcomes of Monte Carlo simulations. We compare industry-standard pseudo-random number generators (PRNGs…

quant-ph2024

Quantum Monte Carlo Integration for Simulation-Based Optimisation

Jingjing Cui, Philippe J. S. de Brouwer, Steven Herbert +7

We investigate the feasibility of integrating quantum algorithms as subroutines of simulation-based optimisation problems with relevance to and potential applications in mathematic…

quant-ph2024

Predicting Ising Model Performance on Quantum Annealers

Salvatore Certo, Georgios Korpas, Andrew Vlasic +1

By analyzing the characteristics of hardware-native Ising Models and their performance on current and next generation quantum annealers, we provide a framework for determining the…