Quantum annealing feature selection on light-weight medical image datasets
Scientific Reports Nature Research 15:1 (2025) 28937
Abstract:
We investigate the use of quantum computing algorithms on real quantum hardware to tackle the computationally intensive task of feature selection for light-weight medical image datasets. Feature selection is often formulated as a k of n selection problem, where the complexity grows binomially with increasing k and n. Quantum computers, particularly quantum annealers, are well-suited for such problems, which may offer advantages under certain problem formulations. We present a method to solve larger feature selection instances than previously demonstrated on commercial quantum annealers. Our approach combines a linear Ising penalty mechanism with subsampling and thresholding techniques to enhance scalability. The method is tested in a toy problem where feature selection identifies pixel masks used to reconstruct small-scale medical images. We compare our approach against a range of feature selection strategies, including randomized baselines, classical supervised and unsupervised methods, combinatorial optimization via classical and quantum solvers, and learning-based feature representations. The results indicate that quantum annealing-based feature selection is effective for this simplified use case, demonstrating its potential in high-dimensional optimization tasks. However, its applicability to broader, real-world problems remains uncertain, given the current limitations of quantum computing hardware. While learned feature representations such as autoencoders achieve superior reconstruction performance, they do not offer the same level of interpretability or direct control over input feature selection as our approach.New nonrenormalization theorem from UV/IR mixing
Physical Review D 110:12 (2024)
Abstract:
In this paper, we prove a new nonrenormalization theorem which arises from UV/IR mixing. This theorem and its corollaries are relevant for all four-dimensional perturbative tachyon-free closed string theories which can be realized from higher-dimensional theories via geometric compactifications. As such, our theorem therefore holds regardless of the presence or absence of spacetime supersymmetry and regardless of the gauge symmetries or matter content involved. This theorem resolves a hidden clash between modular invariance and the process of decompactification, and enables us to uncover a number of surprising phenomenological properties of these theories. Chief among these is the fact that certain physical quantities within such theories cannot exhibit logarithmic or power-law running and instead enter an effective fixed-point regime above the compactification scale. This cessation of running occurs as the result of the UV/IR mixing inherent in the theory. These effects apply not only for gauge couplings but also for the Higgs mass and other quantities of phenomenological interest, thereby eliminating the logarithmic and/or power-law running that might have otherwise appeared for such quantities. These results illustrate the power of UV/IR mixing to tame divergences - even without supersymmetry - and reinforce the notion that UV/IR mixing may play a vital role in resolving hierarchy problems without supersymmetry.Enhancing the Energy Gap of Random Graph Problems via XX-catalysts in Quantum Annealing
ArXiv 2409.1635 (2024)
Running of gauge couplings in string theory
Physical Review D 107:12 (2023)