Zero and Finite Temperature Quantum Simulations Powered by Quantum Magic

We present a comprehensive approach to quantum simulations at both zero and finite temperatures, employing a quantum information theoretic perspective and utilizing the Clifford + $k$Rz transformations. We introduce the "quantum magic ladder", a natural hierarchy formed by systematically augmenting Clifford transformations with the addition of Rz gates. These classically simulable similarity transformations allow us to reduce the quantumness of our system, conserving vital quantum resources. This reduction in quantumness is essential, as it simplifies the Hamiltonian and shortens physical circuit-depth, overcoming constraints imposed by limited error correction. We improve the performance of both digital and analog quantum computers on ground state and finite temperature molecular simulations, not only outperforming the Hartree-Fock solution, but also achieving consistent improvements as we ascend the quantum magic ladder. By facilitating more efficient quantum simulations, our approach enables near-term and early fault-tolerant quantum computers to address novel challenges in quantum chemistry.Comment: 12 pages, 9 figure

A Federated Learning Framework for Stenosis Detection

This study explores the use of Federated Learning (FL) for stenosis detection in coronary angiography images (CA). Two heterogeneous datasets from two institutions were considered: Dataset 1 includes 1219 images from 200 patients, which we acquired at the Ospedale Riuniti of Ancona (Italy); Dataset 2 includes 7492 sequential images from 90 patients from a previous study available in the literature. Stenosis detection was performed by using a Faster R-CNN model. In our FL framework, only the weights of the model backbone were shared among the two client institutions, using Federated Averaging (FedAvg) for weight aggregation. We assessed the performance of stenosis detection using Precision (P rec), Recall (Rec), and F1 score (F1). Our results showed that the FL framework does not substantially affects clients 2 performance, which already achieved good performance with local training; for client 1, instead, FL framework increases the performance with respect to local model of +3.76%, +17.21% and +10.80%, respectively, reaching P rec = 73.56, Rec = 67.01 and F1 = 70.13. With such results, we showed that FL may enable multicentric studies relevant to automatic stenosis detection in CA by addressing data heterogeneity from various institutions, while preserving patient privacy

Antagonistic Mixing in Micelles of Amphiphilic Polyoxometalates and Hexaethylene Glycol Monododecyl Ether

International audienceHypothesis: Polyoxometalates (POMs) are metal oxygen clusters with a range of interesting magnetic and catalytic properties. POMs with attached hydrocarbon chains show amphiphilic behaviour so we hypothesised that mixtures of a nonionic surfactant and anionic surfactants with a polyoxometalate cluster as headgroup would form mixed micelles, giving control of the POM density in the micelle, and which would differ in size and shape from micelles formed by the individual surfactants. Due to the high charge and large size of the POM, we suggested that these would be nonideal mixtures due to the complex interactions between the two types of surfactants. The nonideality and the micellar composition may be quantified using regular solution theory. With supplementary information provided by small-angle neutron scattering (SANS), an understanding of this unusual binary surfactant system can be established.Experiments: A systematic study was performed on mixed surfactant systems containing polyoxometalate-headed amphiphiles (K10[P2W17O61OSi2(CnH(2n+1))2], abbreviated as P2W17-2Cn, where n = 12, 14 or 16) and hexaethylene glycol monododecyl ether (C12EO6). Critical micelle concentrations (CMCs) of these mixtures were measured and used to calculate the interaction parameters based on regular solution theory, enabling prediction of micellar composition. Predictions were compared to micelle structures obtained from SANS. A phase diagram was also established.Findings: The CMCs of these mixtures suggest unusual unfavourable interactions between the two species despite formation of mixed micelles. Micellar compositions obtained from SANS concurred with those calculated using the averaged interaction parameters for P2W17-2Cn/C12EO6 (n = 12 and 14). We attribute the unfavourable interactions to a combination of different phenomena: counterion-mediated interactions between P2W17 units and the unfolding of the ethylene oxide headgroups of the nonionic surfactant, yet micelles still form in these systems due to the hydrophobic interactions between surfactant tails