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Implementation of Support Vector Machines using Reaction Networks

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arXiv 2025年

作者： Choudhary, Amey Jin, Jiaxin Deshpande, Abhishek Center for Computational Natural Sciences and Bioinformatics International Institute of Information Technology Hyderabad India Department of Mathematics University of Louisiana United States

Can machine learning algorithms be implemented using chemical reaction networks? We demonstrate that this is possible in the case of support vector machines (SVMs). SVMs are powerful tools for data classification, leveraging VC theory to handle high-dimensional data and small datasets effectively. In this work, we propose a reaction network scheme for implementing SVMs, utilizing the steady-state behavior of reaction network dynamics to model key computational aspects of SVMs. This approach introduces a novel biochemical framework for implementing machine learning algorithms in non-traditional computational environments. © 2025, CC BY.

关键词： Adversarial machine learning

Emergent non-Markovianity and dynamical quantification of the quantum switch

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Physical Review A 2025年第3期111卷 032428-032428页

作者： Vishal Anand Ananda G. Maity Subhadip Mitra Samyadeb Bhattacharya Center for Security Theory and Algorithmic Research International Institute of Information Technology Gachibowli Hyderabad 500032 India Center for Computational Natural Sciences and Bioinformatics International Institute of Information Technology Gachibowli Hyderabad 500032 India Center for Quantum Science and Technology International Institute of Information Technology Gachibowli Hyderabad 500032 India

We investigate the dynamical aspects of the quantum switch and find a particular form of quantum memory emerging out of the switch action. We first analyze the loss of information in a general quantum evolution subjected to a quantum switch and propose a measure to quantify the switch-induced memory. We then derive an uncertainty relation between information loss and switch-induced memory. We explicitly consider the example of depolarizing dynamics and show how it is affected by the action of a quantum switch. For a more detailed analysis, we consider both the control qubit and the final measurement on the control qubit as noisy and investigate the said uncertainty relation. Further, while deriving the Lindblad-type dynamics for the reduced operation of the switch action, we identify that the switch-induced memory actually leads to the emergence of non-Markovianity. Interestingly, we demonstrate that the emergent non-Markovianity can be explicitly attributed to the switch operation by comparing it with other standard measures of non-Markovianity. Our investigation thus paves the way forward to understanding the quantum switch as an emerging non-Markovian quantum memory.

关键词： Qubits

Decomposable and essentially univariate mass-action systems: Extensions of the deficiency one theorem

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arXiv 2025年

作者： Deshpande, Abhishek Müller, Stefan Center for Computational Natural Sciences and Bioinformatics International Institute of Information Technology Telangana Hyderabad500032 India Faculty of Mathematics University of Vienna Oskar-Morgenstern-Platz 1 Wien1090 Austria

The classical and extended deficiency one theorems by Feinberg apply to reaction networks with mass-action kinetics that have independent linkage classes or subnetworks, each with a deficiency of at most one and exactly one terminal strong component. The theorems assume the existence of a positive equilibrium and guarantee the existence of a unique positive equilibrium in every stoichiometric compatibility class. In our work, we use the monomial dependency which extends the concept of deficiency. First, we provide a dependency one theorem for parametrized systems of polynomial equations that are essentially univariate and decomposable. As our main result, we present a corresponding theorem for mass-action systems, which permits subnetworks with arbitrary deficiency and arbitrary number of terminal strong components. Finally, to complete the picture, we derive the extended deficiency one theorem as a special case of our more general dependency one theorem. Copyright © 2025, The Authors. All rights reserved.

关键词： Polynomials

Topological phase transition in antisymmetric Lotka-Volterra doublet chain

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Physical Review E 2025年第2期111卷 L022203-L022203页

作者： Rukmani Bai Sourin Chatterjee Ujjwal Shekhar Abhishek Deshpande Sirshendu Bhattacharyya Chittaranjan Hens Institut für Theoretische Physik Leibniz Universität Hannover Appelstrasse 2 D-30167 Hannover Germany Institute for Theoretical Physics III and Center for Integrated Quantum Science and Technology University of Stuttgart 70550 Stuttgart Germany Department of Mathematics Statistics Indian Institute of Science Education and Research Kolkata West Bengal 741246 India Institut de Neurosciences des Systèmes (INS) UMR1106 Aix-Marseille Université Marseille France Center for Computational Natural Sciences and Bioinformatics International Institute of Information Technology Gachibowli Hyderabad 500032 India Department of Physics Raja Rammohun Roy Mahavidyalaya Radhanagar Hooghly 712406 India

We present the emergence of topological phase transition in the minimal model of two-dimensional rock-paper-scissors cycle in the form of a doublet chain. The evolutionary dynamics of the doublet chain is obtained by solving the anti-symmetric Lotka-Volterra equation. We show that the mass decays exponentially towards edges and robust against small perturbation in the rate of change of mass transfer, a signature of a topological phase. For one of the configuration of our doublet chain, the mass is transferred towards both edges and the bulk is gaped. Further, we confirm this phase transition within the framework of topological band theory. For this, we calculate the winding number, which change from zero to one for trivial and nontrivial topological phases, respectively.

关键词： Topology

The Computation of the Disguised Toric Locus of Reaction Networks

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arXiv 2025年

作者： Craciun, Gheorghe Deshpande, Abhishek Jin, Jiaxin Department of Mathematics Department of Biomolecular Chemistry University of Wisconsin-Madison United States Center for Computational Natural Sciences and Bioinformatics International Institute of Information Technology Hyderabad India Department of Mathematics University of Louisiana Lafayette United States

Mathematical models of reaction networks can exhibit very complex dynamics, including multistability, oscillations, and chaotic dynamics. On the other hand, under some additional assumptions on the network or on parameters values, these models may actually be toric dynamical systems, which have remarkably stable dynamics. The concept of "disguised toric dynamical system" was introduced in order to describe the phenomenon where a reaction network generates toric dynamics without actually being toric;such systems enjoy all the stability properties of toric dynamical systems but with much fewer restrictions on the networks and parameter values. The disguised toric locus is the set of parameter values for which the corresponding dynamical system is a disguised toric system. Here we focus on providing a generic and efficient method for computing the dimension of the disguised toric locus of reaction networks. Additionally, we illustrate our approach by applying it to some specific models of biological interaction networks, including Brusselator-type networks, Thomas-type networks, and circadian clock networks. © 2025, CC BY.

关键词： Dynamics

Weakly reversible deficiency zero realizations of reaction networks

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arXiv 2025年

作者： Buxton, Neal Craciun, Gheorghe Deshpande, Abhishek Pantea, Casian Department of Mathematics West Virginia University United States Department of Mathematics Department of Biomolecular Chemistry University of Wisconsin-Madison United States Center for Computational Natural Sciences and Bioinformatics International Institute of Information Technology Hyderabad India

We prove that if a given reaction network N has a weakly reversible deficiency zero realization for all choice of rate constants, then there exists a unique weakly reversible deficiency zero network N′ such that N is realizable by N′. Additionally, we propose an algorithm to find this weakly reversible deficiency zero network N′ when it *** Codes 37N25, 92C42, 80A30, 92D25, 92C45 Copyright © 2025, The Authors. All rights reserved.

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Right-handed neutrino production through first-generation leptoquarks

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Physical Review D 2025年第7期111卷 075032-075032页

作者： Gokul Duraikandan Rishabh Khanna Tanumoy Mandal Subhadip Mitra Rachit Sharma Indian Institute of Science Education and Research Thiruvananthapuram Vithura Kerala 695 551 India Center for Computational Natural Sciences and Bioinformatics International Institute of Information Technology Hyderabad 500 032 India Center for Quantum Science and Technology International Institute of Information Technology Hyderabad 500 032 India

The collider phenomenology of leptoquarks (LQs) and right-handed neutrinos (RHNs) has been studied extensively in the literature. Due to their gauge singlet nature, the production of RHNs at the LHC is typically suppressed by the tiny light-heavy neutrino mixing angles. In this study, we explore a promising scenario where the presence of a LQ mediator significantly enhances the RHN production: the LQ essentially couples only to first-generation fermions (quarks and leptons, including the RHN), and the coupling with the first-generation RHN dominates. We consider all possible scalar and vector LQs that could lead to such a scenario. The prospects are better for the first-generation scenario than the other generations because of the enhanced parton distribution functions (PDFs) of first-generation quarks. The enhanced PDFs boost the production cross sections of LQs, particularly their single and indirect productions. Incorporating all production modes of LQs that result in a pair of RHNs, we estimate the discovery prospects by analyzing the monoelectron and dielectron channels arising from the decay of the RHN pair. We find that the indirect production of LQs is crucial in determining the discovery reach at the HL-LHC for the first-generation scenario.

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Contrasting Low and High-Resolution Features for HER2 Scoring using Deep Learning

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arXiv 2025年

作者： Chauhan, Ekansh Sharma, Anila Sharma, Amit Nishadham, Vikas Ghughtyal, Asha Kumar, Ankur Gupta, Gurudutt Mehta, Anurag Jawahar, C.V. Vinod, P.K. Centre for Visual Information Technology International Institute of Information Technology Telangana Hyderabad500032 India Department of Pathology Rajiv Gandhi Cancer Institute & Research Centre Delhi New Delhi110085 India Center for Computational Natural Sciences and Bioinformatics International Institute of Information Technology Telangana Hyderabad500032 India

Breast cancer, the most common malignancy among women, requires precise detection and classification for effective treatment. Immunohistochemistry (IHC) biomarkers like HER2, ER, and PR are critical for identifying breast cancer subtypes. However, traditional IHC classification relies on pathologists’ expertise, making it labor-intensive and subject to significant inter-observer variability. To address these challenges, this study introduces the India Pathology Breast Cancer Dataset (IPD-Breast), comprising of 1,272 IHC slides (HER2, ER, and PR) aimed at automating receptor status classification. The primary focus is on developing predictive models for HER2 3-way classification (0, Low, High) to enhance prognosis. Evaluation of multiple deep learning models revealed that an end-to-end ConvNeXt network utilizing low-resolution IHC images achieved an AUC, F1, and accuracy of 91.79%, 83.52%, and 83.56%, respectively, for 3-way classification, outperforming patch-based methods by over 5.35% in F1 score. This study highlights the potential of simple yet effective deep learning techniques to significantly improve accuracy and reproducibility in breast cancer classification, supporting their integration into clinical workflows for better patient outcomes. © 2025, CC0.

关键词： Lung cancer

Vector leptoquark contributions to lepton dipole moments

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Physical Review D 2025年第1期111卷 015045-015045页

作者： Arvind Bhaskar Diganta Das Soumyadip Kundu Anirudhan A. Madathil Tanumoy Mandal Subhadip Mitra Institute of Physics Sachivalaya Marg Bhubaneswar 751 005 India Center for Computational Natural Sciences and Bioinformatics International Institute of Information Technology Hyderabad 00 032 India Indian Institute of Science Education and Research Thiruvananthapuram Vithura Kerala 695 551 India Department of Physics and Astronomy University of Utah Salt Lake City Utah 84112 USA Center for Quantum Science and Technology International Institute of Information Technology Hyderabad 00 032 India

Leptoquarks (LQs) can contribute to the magnetic and electric dipole moments of charged leptons, which the current experiments have measured with good accuracy. We revisit the parameter spaces of TeV-scale vector LQs that contribute to these observables and study how these models fare against the LHC bounds. We show that significant portions of the parameter space are excluded when the current LHC data is utilized effectively. We find that only U1 and V2 can explain the observed positive shift in (aμexp−aμSM) through a lepton chirality-flipping contribution with O(1) LQ-quark-lepton coupling. We also see how these two LQs can fit the electron dipole moment and atomic parity violation measurements. We find that the current electric dipole moment measurements of the muon cannot restrain the LQ-quark-lepton couplings within perturbative regions.

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