7 papers
Orthogonal Quantum Krylov Diagonalisation
Hadi Rammal, Alexandre Perrin, Oumaya Ladhari +3
Quantum subspace-diagonalization methods, particularly Quantum Krylov Diagonalization (QKD), provide a promising route for computing low-energy spectra of quantum many-body Hamilto…
Refining Quantum Phase Estimation Precision Conditions on Unitaries for Many-Electron Systems
Jérémie Messud, Wassil Sennane
Beyond ground state energy estimation, quantum phase estimation (QPE) applied to many-electron systems has the potential to output an approximation of the ground state, enabling in…
On the robustness of Quantum Phase Estimation to compute ground properties of many-electron systems
Wassil Sennane, Jérémie Messud
We propose an analysis of the Quantum Phase Estimation (QPE) algorithm applied to many-electron systems by investigating its free parameters such as the time step, number of phase…
From quantum to quantum-inspired: the LogQ algorithm as a non-linear continuous relaxation of variables method
Jérémie Messud, Yagnik Chatterjee
The LogQ algorithm encodes Quadratic Unconstrained Binary Optimization (QUBO) problems, which are often encountered in the industry (portfolio optimization, fleet optimization, cha…
Portfolio Optimization with 'Physical' Decision Variables and Non-Linear Performance Metrics: Diversification Challenge and Proposals
Isabel Barros Garcia, Jérémie Messud
Portfolio optimization (PO) is a core tool in financial and operational decision-making, typically balancing expected profit and risk. In real-world applications, particularly in t…
Unified Approach to Portfolio Optimization using the `Gain Probability Density Function' and Applications
Jean-Patrick Mascomère, Jérémie Messud, Yagnik Chatterjee +1
This article proposes a unified framework for portfolio optimization (PO), recognizing an object called the `gain probability density function (PDF)' as the fundamental object of t…