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Abhishek Deshpande

Publications and source records attributed to Abhishek Deshpande.

At least 19 recordsLinked to original sources

Implementation of Linear Regression and Linear Interpolation using Reaction Networks

Statistical inference is a fundamental component of data science. In this work, we focus on two classical inference techniques: regression and interpolation. We propose a reaction-network-based framework for implementing linear regression, including both univariate and multivariate settings, as well as linear interpolation. Our approach encodes the outputs of these inference techniques in the steady-state concentrations of species within the reaction network. A key ingredient of the construction is a novel generalized division module capable of handling division involving negative numbers. We validate the proposed framework through in silico implementations on standard synthetic datasets and obtain the expected regression and interpolation outputs.

q-bio.MN↗

Disguised complex balance via positive algebraic geometry

We study dynamical systems arising from reaction networks under mass-action kinetics. For certain choices of the rate constants (parameters), such systems are complex-balanced (vertex-balanced), which guarantees the existence of a unique positive equilibrium. Moreover, this equilibrium is asymptotically stable (admitting a global Lyapunov function) and linearly stable. In a series of recent papers, Craciun and collaborators introduced and studied disguised complex-balanced systems, that is, mass-action systems that are dynamically equal to auxiliary complex-balanced systems and therefore inherit their strong stability properties. Determining the parameter values for which a given system is disguised complex-balanced is a nontrivial algebraic problem. In this work, we show that the defining conditions for disguised complex-balanced equilibria naturally give rise to parametrized systems of polynomial inequalities. Using the framework for positive algebraic geometry developed by Müller and Regensburger, we reformulate these systems as binomial equations (on the disguised complex-balanced flux cone). Computing the disguised complex-balanced parameter locus can be viewed as a quantifier-elimination problem, and our approach eliminates the concentrations (state variables) from the problem. We illustrate our results using the running example of a recent paper by Boros et al.

math.DS↗

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

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 absorbing 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 $\textit{monomial dependency}$ 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 absorbing 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.

math.DS↗

Existence of a unique, nondegenerate solution to parametrized systems of generalized polynomial equations

We consider parametrized systems of generalized polynomial equations (with real exponents) in $n$ positive variables, involving $m$ monomials with positive parameters; that is, $x\in\mathbb{R}^n_>$ such that ${A \, (c \circ x^B)=0}$ with coefficient matrix $A\in\mathbb{R}^{l \times m}$, exponent matrix $B\in\mathbb{R}^{n \times m}$, parameter vector $c\in\mathbb{R}^m_>$ (and componentwise product $\circ$). Our main result characterizes the existence of a unique, nondegenerate solution (up to an exponential manifold) for all parameters in terms of the relevant geometric objects of the polynomial system: the $\textit{coefficient polytope}$ and the $\textit{monomial dependency subspace}$. Technically, we show that unique existence of a nondegenerate solution is equivalent to a composite (monomial-exponential moment) map being a diffeomorphism, and we characterize this property using Hadamard's global inversion theorem. Additionally, we provide sufficient conditions in terms of sign vectors of the geometric objects, which represent a genuine multivariate generalization of Descartes' rule of signs for exactly one solution. Finally, we illustrate all objects and results in a concrete example.

math.AG↗

Mean-Field and Pairwise Approaches for the SIRI Model on Poisson Networks

Compartmental epidemic models, grounded in mass-action kinetics, often assume homogeneous mixing. Although this neglects network structure, recent results show that for Poisson random graphs, the classical SIR model, especially the susceptible decay curve, matches the susceptible decay dynamics of its network counterpart. Motivated by this, we investigate whether the extended SIRI model with relapse from the recovered class admits a similar correspondence. SIRI dynamics arise in sevaral scenarios like spread of diseases with reactivation and behavioral contagion with relapse. We derive parameter relationships under which the pairwise SIRI model on a Poisson network closely follows the mass-action ODE trajectories. When transmission per contact is small relative to recovery, the susceptible and infectious trajectories of both systems align. This establishes conditions under which nonlinear SIRI dynamics on networks can be effectively approximated by tractable mean-field equations.

q-bio.PE↗

Implementation of Support Vector Machines using Reaction Networks

Can machine learning algorithms be implemented using chemistry? We demonstrate that this is possible in the case of support vector machines (SVMs). SVMs are powerful tools for data classification, leveraging Vapnik-Chervonenkis theory to handle high-dimensional data and small datasets effectively. In this work, we propose a chemical 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.

q-bio.MN↗

AI-Ready Control System for the Fermilab Accelerator Complex

Reliable, high-intensity operation of the Fermilab Accelerator Complex is critical to the success of the Long-Baseline Neutrino Facility and Deep Underground Neutrino Experiment. We describe the requirements and infrastructure necessary to support routine use of artificial intelligence and machine learning (AI/ML) in the accelerator control system. Three capabilities are identified: a machine learning operations (MLOps) framework standardizing the lifecycle of AI/ML automation from data management through deployment and monitoring; a data quality framework defining and enforcing standards required to build trustworthy AI/ML applications; and workflow integration with large language models to assist physicists, engineers, and operators with information retrieval, code development, and routine analysis. Use cases spanning beam diagnostics, beam control, and support system automation illustrate the technical requirements across the complex.

physics.acc-ph↗

Extinction in Reaction Network Models

In this paper, we study extinction in dynamical systems generated by reaction networks. We introduce two notions: weak extinction and strong extinction, and relate them to the structure of the underlying network through Lyapunov functions and LaSalle's invariance principle. In particular, for all deficiency-zero networks that are not weakly reversible, we provide a geometric construction of linear Lyapunov functions. Using these functions, we establish that if these networks have bounded invariant subspaces, then they must exhibit weak extinction within every such subspace. Also, for linear networks that are not weakly reversible, we show that every species outside a terminal strongly connected component undergoes strong extinction. Moreover, in order to further emphasize the difference between weak and strong extinction, we construct an example of a reaction system (based on the Ivanova network) that exhibits weak extinction for all the species, but does not exhibit strong extinction in any species.

math.DS↗

The Computation of the Disguised Toric Locus of Reaction Networks

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 parameter 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 \emph{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.

math.DS↗

Weakly reversible deficiency zero realizations of reaction networks

We prove that if a given reaction network $\mathcal{N}$ has a weakly reversible deficiency zero realization for all choice of rate constants, then there exists a $\textit{unique}$ weakly reversible deficiency zero network $\mathcal{N}'$ such that $\mathcal{N}$ is realizable by $\mathcal{N}'$. Additionally, we propose an algorithm to find this weakly reversible deficiency zero network $\mathcal{N}'$ when it exists.

q-bio.MN↗

The Dimension of the Disguised Toric Locus of a Reaction Network

Under mass-action kinetics, complex-balanced systems emerge from biochemical reaction networks and exhibit stable and predictable dynamics. For a reaction network $G$, the associated dynamical system is called $\textit{disguised toric}$ if it can yield a complex-balanced realization on a possibly different network $G_1$. This concept extends the robust properties of toric systems to those that are not inherently toric. In this work, we study the $\textit{disguised toric locus}$ of a reaction network - i.e., the set of positive rate constants that make the corresponding mass-action system disguised toric. Our primary focus is to compute the exact dimension of this locus. We subsequently apply our results to Thomas-type and circadian clock models.

q-bio.MN↗

Topological phase transition in anti-symmetric Lotka-Volterra doublet chain

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 a non-trivial topological phases respectively.

cond-mat.stat-mech↗

Realizations through Weakly Reversible Networks and the Globally Attracting Locus

We investigate the possibility that for any given reaction rate vector $k$ associated with a network $G$, there exists another network $G'$ with a corresponding reaction rate vector that reproduces the mass-action dynamics generated by $(G,k)$. Our focus is on a particular class of networks for $G$, where the corresponding network $G'$ is weakly reversible. In particular, we show that strongly endotactic two-dimensional networks with a two dimensional stoichiometric subspace, as well as certain endotactic networks under additional conditions, exhibit this property. Additionally, we establish a strong connection between this family of networks and the locus in the space of rate constants of which the corresponding dynamics admits globally stable steady states.

math.DS↗

Flow Induced Corrosion in 6061-T6 Aluminum Pipes in De-Ionized Water Environments

Flow induced corrosion/erosion of 6061-T6 aluminum in de-ionized (DI) water environments has not been studied widely. Especially, the long-term effects of corrosion/erosion in seemingly benign flow velocity, temperature, and resistivity ranges of 8 ft/s, 85 oF, 3-5 MOhm-cm, respectively. This study concludes that the flow induced corrosion/erosion in the above parameter ranges is minimal. This is detailed by presenting a literature survey, measuring pipe wall samples from a system that has operated in the above parameter range, predict the loss of material in mm/year at the above velocities and at higher temperatures using electric potential values from other experimental studies coupled with wall shear stress simulated using Computational Fluid Dynamic (CFD) analysis.

physics.acc-ph↗

On the Connectivity of the Disguised Toric Locus of a Reaction Network

Complex-balanced mass-action systems are some of the most important types of mathematical models of reaction networks, due to their widespread use in applications, as well as their remarkable stability properties. We study the set of positive parameter values (i.e., reaction rate constants) of a reaction network $G$ that, according to mass-action kinetics, generate dynamical systems that can be realized as complex-balanced systems, possibly by using a different graph $G'$. This set of parameter values is called the disguised toric locus of $G$. The $\mathbb{R}$-disguised toric locus of $G$ is defined analogously, except that the parameter values are allowed to take on any real values. We prove that the disguised toric locus of $G$ is path-connected, and the $\mathbb{R}$-disguised toric locus of $G$ is also path-connected. We also show that the closure of the disguised toric locus of a reaction network contains the union of the disguised toric loci of all its subnetworks.

math.DS↗

A Lower Bound on the Dimension of the $\mathbb{R}$-Disguised Toric Locus of a Reaction Network

Polynomial dynamical systems (i.e. dynamical systems with polynomial right hand side) are ubiquitous in applications, especially as models of reaction networks and interaction networks. The properties of general polynomial dynamical systems can be very difficult to analyze, due to nonlinearity, bifurcations, and the possibility for chaotic dynamics. On the other hand, toric dynamical systems are polynomial dynamical systems that appear naturally as models of reaction networks, and have very robust and stable properties. A disguised toric dynamical system is a polynomial dynamical system generated by a reaction network $\mathcal N$ and some choice of positive parameters, such that (even though it may not be toric with respect to $\mathcal N$) it has a toric realization with respect to some network $\mathcal N'$. Disguised toric dynamical systems enjoy all the robust stability properties of toric dynamical systems. In this paper, we study a larger set of dynamical systems where the rate constants are allowed to take both positive and negative values. More precisely, we analyze the $\mathbb{R}$-disguised toric locus of a reaction network $\mathcal N$, i.e., the subset in the space rate constants (positive or negative) of $\mathcal N$ for which the corresponding polynomial dynamical system is disguised toric. We focus especially on finding a lower bound on the dimension of the $\mathbb{R}$-disguised toric locus.

math.DS↗

Weakly reversible deficiency one realizations of polynomial dynamical systems: an algorithmic perspective

Given a dynamical system with polynomial right-hand side, can it be generated by a reaction network that possesses certain properties? This question is important because some network properties may guarantee specific dynamical properties, such as existence or uniqueness of equilibria, persistence, permanence, or global stability. Here we focus on this problem in the context of weakly reversible deficiency one networks. In particular, we describe an algorithm for deciding if a polynomial dynamical system admits a weakly reversible deficiency one realization, and identifying one if it does exist. In addition, we show that weakly reversible deficiency one realizations can be partitioned into mutually exclusive Type I and Type II realizations, where Type I realizations guarantee existence and uniqueness of positive steady states, while Type II realizations are related to stoichiometric generators, and therefore to multistability.

math.DS↗

Endotactic and strongly endotactic networks with infinitely many positive steady states

We show that there exists endotactic and strongly endotactic dynamical systems that are not weakly reversible and possess infinitely many steady states. We provide a few examples in two dimensions and an example in three dimensions that satisfy this property. In addition, we prove for some of these systems that there exist no weakly reversible mass-action systems that are dynamically equivalent to mass-action systems generated by these networks.

math.DS↗