14 citations · 17 across the 12 of their papers we have counts for
12 papers
Semidefinite optimization as many-body thermodynamics: Boltzmann, Fermi-Dirac, and Bose-Einstein frameworks
Michele Minervini, Nana Liu, Dhrumil Patel +1
We study the semidefinite programs (SDPs) of quantum information whose variables are density operators, measurement operators, or unbounded positive semidefinite operators, togethe…
Quantum Spectral Anomaly Detection
Yewei Yuan, Michele Minervini, Mark M. Wilde +1
A core task in quantum anomaly detection is to compute an anomaly score that quantifies how strongly a test quantum state deviates from a given quantum dataset assumed to be normal…
Canonical quantization of neurons
Alexander He, Nana Liu, Mark M. Wilde
Canonical quantization provides a systematic procedure for constructing quantum models from classical Hamiltonians. Here, we apply this principle to a fundamental computational pri…
Analog photonic simulator for large-scale transport
Mengyu Zhao, Xuezhi Zhu, Nikita Guseynov +9
Transport equations describe how physical quantities -- such as mass, energy, momentum, concentration, probability, or fields -- are carried, propagated, or redistributed through s…
Quantum principal component analysis without eigenvector recovery
Yewei Yuan, Michele Minervini, Mark M. Wilde +1
Principal component analysis (PCA) is traditionally implemented through a covariance or kernel matrix, leading-eigenvector extraction, and hard rank- projection. These steps can…
Bose-Einstein thermal operators for semidefinite optimization
Michele Minervini, Nana Liu, Mark M. Wilde
We establish that semidefinite programs (SDPs) over the unbounded positive semidefinite cone are mathematically equivalent to thermodynamic systems of independent bosonic modes: th…
End-to-End PDE-Based Quantum Algorithms for Multi-Asset Option Pricing under Local and Stochastic Volatility
Nikita Guseynov, Nana Liu, Chi Seng Pun +1
Multi-asset option pricing under local- and stochastic-volatility models leads naturally to high-dimensional parabolic PDEs. We develop an end-to-end quantum PDE framework for Euro…
Fermi-Dirac machines as quantizations of neurons
Alexander He, Nana Liu, Mark M. Wilde
Fermi-Dirac machines were proposed recently as an approach to solving semidefinite optimization problems on quantum computers. Here, we reinterpret them as canonical quantizations…
Quantum Algorithm for Local-Volatility Option Pricing via the Kolmogorov Equation
Nikita Guseynov, Mikel Sanz, Ángel Rodríguez-Rozas +2
The solution of option-pricing problems may turn out to be computationally demanding due to non-linear and path-dependent payoffs, the high dimensionality arising from multiple und…
Quantum Framework for Simulating Linear PDEs with Robin Boundary Conditions
Nikita Guseynov, Xiajie Huang, Nana Liu
We propose an explicit, oracle-free quantum framework for numerically simulating general linear partial differential equations (PDEs), extending previous work to incorporate (a) Ro…
Efficient explicit circuit for quantum state preparation of piecewise continuous functions
Nikita Guseynov, Nana Liu
Efficiently uploading data into quantum states is essential for many quantum algorithms to achieve advantage across various applications. In this paper, we address this challenge b…
Efficient explicit gate construction of block-encoding for Hamiltonians needed for simulating partial differential equations
Nikita Guseynov, Xiajie Huang, Nana Liu
One of the most promising applications of quantum computers is solving partial differential equations (PDEs). By using the Schrodingerisation technique - which converts non-conserv…