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Search · four archives
22 papers · ranked by Valyu relevance
Namasi G Sankar, Georgios Miliotis, Simon Caton
Genome assembly is important in infectious disease surveillance, antimicrobial resistance monitoring, and cancer genomics. The task of reconstructing full genomic sequences from fragmented reads, can be framed as a large scale combinatorial optimisation problem. Recent advances in quantum computing have introduced new…
Raphaël Côte, Emmanuel Franck, Laurent Navoret, Guillaume Steimer + 1 more
'Vincent Vigon'] The reduction of Hamiltonian systems aims to build smaller reduced models, valid over a certain range of time and parameters, in order to reduce computing time. By maintaining the Hamiltonian structure in the reduced model, certain long-term stability properties can be preserved. In this paper, we…
Süleyman Yıldız, Pawan Goyal, Thomas Bendokat, Peter Benner
We present a framework for learning Hamiltonian systems using data. This work is based on a lifting hypothesis, which posits that nonlinear Hamiltonian systems can be written as nonlinear systems with cubic Hamiltonians. By leveraging this, we obtain quadratic dynamics that are Hamiltonian in a transformed coordinate…
Federico Zadra, Marcello Seri
> In this paper, we explore the relationship between dynamical symmetries, Cartan symmetries, and dynamical similarities in contact mechanics. Using an alternative decomposition of vector fields, we provide a characterization of those symmetries and a new description in terms of tensor densities. Additionally, we show…
Joshua Erde, Florian Lehner
A well-known conjecture of Alspach says that every -regular Cayley graph of a finite abelian group can be decomposed into Hamiltonian cycles. We consider an analogous question for infinite abelian groups. In this setting one natural analogue of a Hamiltonian cycle is a spanning double-ray. However, a naive…
A. V. Tsiganov
and some additional relations between (x, t) and (y, τ), which allow to get both equations E and E˜. The BT is called an auto-BT or a hetero-BT depending whether the two PDEs are the same or not. The hetero-BTs describe a correspondence between equations rather than a one-to-one mapping between their solutions [1, 12].…
Marine De Clerck, Oleg Evnin
Gérard and Grellier proposed, under the name of the cubic Szegő equation, a remarkable classical field theory on a circle with a quartic Hamiltonian. The Lax integrability structure that emerges from their definition is so constraining that it allows for writing down an explicit general solution for prescribed initial…
Eryn Sale, Wen-Hao Zhang
The brain lives in an ever-changing world and needs to infer the dynamic evolution of latent states from noisy sensory inputs. Exploring how canonical recurrent neural circuits in the brain realize dynamic inference is a fundamental question in neuroscience. Nearly all existing studies on dynamic inference focus on…
Laurent La Fuente-Gravy
| 1 | Introduction | | 1 | | --- | --- | --- | --- | | 2 | | Star products, derivations and automorphisms | 3 | | | 2.1 | Derivations | 4 | | | 2.2 | Automorphisms | 4 | | 3 | | The group of Hamiltonian automorphisms | 7 | | 4 | | The formal flux morphism | 8 | | 5 | | Paths of Hamiltonian automorphisms | 13 | | 6 | |…
Authors not listed
Molecular polaritons are hybrid states formed by the quantum mechanical interaction between light and matter. Recent experiments have shown the ability to drastically modify chemical reactions in both the ground and excited states through the hybridization of the electronic and photonic degrees of freedom. Ab initio…
Michał Włodarczyk
We introduce the non-commutative subset convolution-a convolution of functions useful when working with determinant-based algorithms. In order to compute it efficiently, we take advantage of Clifford algebras, a generalization of quaternions used mainly in the quantum field theory. We apply this tool to speed up…
Michele Gandolfi, Michele Ceotto
of Artificially Pair-Decoupled Systems: An Accurate Tool for Investigating the Importance of Intramolecular Couplings Authors: ['Michele Gandolfi' 'Michele Ceotto'] We propose a numerical technique to accurately simulate the vibrations of organic molecules in the gas phase, when pairs of atoms (or, in general, groups…
Daniel A. Messenger, Joshua W. Burby, David M. Bortz
Weak form equation learning and surrogate modeling has proven to be computationally efficient and robust to measurement noise in a wide range of applications including ODE, PDE, and SDE discovery, as well as in coarse-graining applications, such as homogenization and mean-field descriptions of interacting particle…
Bharath Raghavan, David M. Rogers
Controllable protein sequence generation remains a central challenge in computational protein design, as most existing approaches rely on retraining, classifier guidance, or architectural modification to impose conditioning. Here we introduce ProtNHF, a generative model that enables continuous, quantitative control…
Authors not listed
Ongoing research involving electronic spin-dependent dynamics, such as chiral- induced spin selectivity, is providing impetus to revise our understanding of nuclear en- tanglement with electronic spatial and spin degrees of freedom. In a spin-independent setting, non-adiabatic couplings are well-known mediators of…
Duncan Bossion, Sutirtha Chowdhury, Pengfei Huo
We present the rigorous theoretical framework of the generalized spin mapping representation for non- adiabatic dynamics. This formalism is based on the generators of the su(N) Lie algebra to represent N discrete electronic states, thus preserving the size of the original Hilbert space in the state representation. The…
Thibault Bonnemain, Vincent Caudrelier, Benjamin Doyon
Generalised hydrodynamics (GHD) describes the large-scale inhomogeneous dynamics of integrable (or close to integrable) systems in one dimension of space, based on a central equation for the fluid density or quasi-particle density: the GHD equation. We consider a new, general form of the GHD equation: we allow for…
Rakesh Sengupta, Anindya Pattanayak, Raju Surampudi Bapi
The stability analysis of dynamical neural network systems generally follows the route of finding a suitable Liapunov function after the fashion Hopfield’s famous paper on content addressable memory network or by finding conditions that make divergent solutions impossible. For the current work we focused on biological…
Authors not listed
In these Notes we present a new perspective on the exact-factorization expression of a molecular wavefunction, which does not rely of the probabilistic interpretation of the molecular wavefunction as a joint probability amplitude. Instead, we demonstrate a close relation with the traditional Born-Huang representation…
Mohammad Aamir Sohail, Ranga R. Sudharshan, S. Sandeep Pradhan, Arvind Rao
We present a new Hamiltonian-learning framework based on time-resolved measurement data from a fixed local IC-POVM and its application to inferring gene regulatory networks. We introduce the quantum Hamiltonian-based gene-expression model (QHGM), in which gene interactions are encoded as a parameterized Hamiltonian…
Authors not listed
This article is the second in a two-part tutorial review on electronic spin-dependent dynamics. In Part I, we presented the fundamental theory within the adiabatic Born– Huang framework that describes the interaction between nuclear motion and the elec- tronic (spin and spatial) degrees of freedom. In particular, we…
Authors not listed
This work establishes theoretical foundations for hierarchical quantum-classical algorithm design, where complex problems are decomposed across multiple spatial, temporal, or organizational scales with quantum and classical computation assigned to appropriate levels. We develop a mathematical framework that…