119 citations · 398 across the 12 of their papers we have counts for
12 papers
Decomposition Pipeline for Large-Scale Portfolio Optimization with Applications to Near-Term Quantum Computing
Atithi Acharya, Romina Yalovetzky, Pierre Minssen +10
Industrially relevant constrained optimization problems, such as portfolio optimization and portfolio rebalancing, are often intractable or difficult to solve exactly. In this work…
Q-CHOP: Quantum constrained Hamiltonian optimization
Michael A. Perlin, Ruslan Shaydulin, Benjamin P. Hall +7
Combinatorial optimization problems that arise in science and industry typically have constraints. Yet the presence of constraints makes them challenging to tackle using both class…
Des-q: a quantum algorithm to provably speedup retraining of decision trees
Niraj Kumar, Romina Yalovetzky, Changhao Li +2
Decision trees are widely adopted machine learning models due to their simplicity and explainability. However, as training data size grows, standard methods become increasingly slo…
Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem
Ruslan Shaydulin, Changhao Li, Shouvanik Chakrabarti +26
The quantum approximate optimization algorithm (QAOA) is a leading candidate algorithm for solving optimization problems on quantum computers. However, the potential of QAOA to tac…
Hardness of the Maximum Independent Set Problem on Unit-Disk Graphs and Prospects for Quantum Speedups
Ruben S. Andrist, Martin J. A. Schuetz, Pierre Minssen +9
Rydberg atom arrays are among the leading contenders for the demonstration of quantum speedups. Motivated by recent experiments with up to 289 qubits [Ebadi et al., Science 376, 12…
Quantum Deep Hedging
El Amine Cherrat, Snehal Raj, Iordanis Kerenidis +12
Quantum machine learning has the potential for a transformative impact across industry sectors and in particular in finance. In our work we look at the problem of hedging where dee…
Universal Quantum Speedup for Branch-and-Bound, Branch-and-Cut, and Tree-Search Algorithms
Shouvanik Chakrabarti, Pierre Minssen, Romina Yalovetzky +1
Mixed Integer Programs (MIPs) model many optimization problems of interest in Computer Science, Operations Research, and Financial Engineering. Solving MIPs is NP-Hard in general,…
Constrained Optimization via Quantum Zeno Dynamics
Dylan Herman, Ruslan Shaydulin, Yue Sun +6
Constrained optimization problems are ubiquitous in science and industry. Quantum algorithms have shown promise in solving optimization problems, yet none of the current algorithms…
Constrained Quantum Optimization for Extractive Summarization on a Trapped-ion Quantum Computer
Pradeep Niroula, Ruslan Shaydulin, Romina Yalovetzky +4
Realizing the potential of near-term quantum computers to solve industry-relevant constrained-optimization problems is a promising path to quantum advantage. In this work, we consi…
Solving Linear Systems on Quantum Hardware with Hybrid HHL++
Romina Yalovetzky, Pierre Minssen, Dylan Herman +1
The limited capabilities of current quantum hardware significantly constrain the scale of experimental demonstrations of most quantum algorithmic primitives. This makes it challeng…
Quantum Machine Learning for Finance
Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar +10
Quantum computers are expected to surpass the computational capabilities of classical computers during this decade, and achieve disruptive impact on numerous industry sectors, part…
The Efficient Preparation of Normal Distributions in Quantum Registers
Arthur G. Rattew, Yue Sun, Pierre Minssen +1
The efficient preparation of input distributions is an important problem in obtaining quantum advantage in a wide range of domains. We propose a novel quantum algorithm for the eff…