29 citations · 149 across the 27 of their papers we have counts for
28 papers
Aging in a two-dimensional swarmalator crystal with delayed interactions
Chanin Kumpeerakij, Thiparat Chotibut, Oleg Kogan
Time delay can have a significant impact on the properties of collective organization of active matter. In the previous paper [1], we discussed delay-induced breathing in a system…
Connecting phases of matter to the flatness of the loss landscape in analog variational quantum algorithms
Kasidit Srimahajariyapong, Supanut Thanasilp, Thiparat Chotibut
Variational quantum algorithms (VQAs) promise near-term quantum advantage, yet parametrized quantum states commonly built from the digital gate-based approach often suffer from sca…
Role of scrambling and noise in temporal information processing with quantum systems
Weijie Xiong, Zoë Holmes, Armando Angrisani +3
Scrambling quantum systems have attracted attention as effective substrates for temporal information processing. Here we consider a quantum reservoir processing framework that capt…
A unifying account of warm start guarantees for patches of quantum landscapes
Hela Mhiri, Ricard Puig, Sacha Lerch +4
Barren plateaus are fundamentally a statement about quantum loss landscapes on average but there can, and generally will, exist patches of barren plateau landscapes with substantia…
Dissipation alters modes of information encoding in small quantum reservoirs near criticality
Krai Cheamsawat, Thiparat Chotibut
Quantum reservoir computing (QRC) has emerged as a promising paradigm for harnessing near-term quantum devices to tackle temporal machine learning tasks. Yet identifying the mechan…
Practical Quantum Circuit Implementation for Simulating Coupled Classical Oscillators
Natt Luangsirapornchai, Peeranat Sanglaor, Apimuk Sornsaeng +4
Simulating large-scale coupled-oscillator systems presents substantial computational challenges for classical algorithms, particularly when pursuing first-principles analyses in th…
CrystalGRW: Generative Modeling of Crystal Structures with Targeted Properties via Geodesic Random Walks
Krit Tangsongcharoen, Teerachote Pakornchote, Chayanon Atthapak +6
Determining whether a candidate crystalline material is thermodynamically stable depends on identifying its true ground-state structure, a central challenge in computational materi…
Interval maps mimicking circle rotations
Jakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski +2
We investigate the dynamics of maps of the real line whose behavior on an invariant interval is close to a rational rotation on the circle. We concentrate on a specific two-paramet…
On fundamental aspects of quantum extreme learning machines
Weijie Xiong, Giorgio Facelli, Mehrad Sahebi +4
Quantum Extreme Learning Machines (QELMs) have emerged as a promising framework for quantum machine learning. Their appeal lies in the rich feature map induced by the dynamics of a…
Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling
Teerachote Pakornchote, Natthaphon Choomphon-anomakhun, Sorrjit Arrerut +4
The crystal diffusion variational autoencoder (CDVAE) is a machine learning model that leverages score matching to generate realistic crystal structures that preserve crystal symme…
Quantum Next Generation Reservoir Computing: An Efficient Quantum Algorithm for Forecasting Quantum Dynamics
Apimuk Sornsaeng, Ninnat Dangniam, Thiparat Chotibut
Next Generation Reservoir Computing (NG-RC) is a modern class of model-free machine learning that enables an accurate forecasting of time series data generated by dynamical systems…
StrainTensorNet: Predicting crystal structure elastic properties using SE(3)-equivariant graph neural networks
Teerachote Pakornchote, Annop Ektarawong, Thiparat Chotibut
Accurately predicting the elastic properties of crystalline solids is vital for computational materials science. However, traditional atomistic scale ab initio approaches are compu…
Quantum state-preparation control in noisy environment via most-likely paths
Wirawat Kokaew, Thiparat Chotibut, Areeya Chantasri
Finding controls for open quantum systems needs to take into account effects from unwanted environmental noise. Since actual realizations or states of the noise are typically unkno…
Unpredictable dynamics in congestion games: memory loss can prevent chaos
Jakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski +2
We study the dynamics of simple congestion games with two resources where a continuum of agents behaves according to a version of Experience-Weighted Attraction (EWA) algorithm. Th…
Explainable Natural Language Processing with Matrix Product States
Jirawat Tangpanitanon, Chanatip Mangkang, Pradeep Bhadola +3
Despite empirical successes of recurrent neural networks (RNNs) in natural language processing (NLP), theoretical understanding of RNNs is still limited due to intrinsically comple…
Hybrid Quantum-Classical Algorithms for Loan Collection Optimization with Loan Loss Provisions
Jirawat Tangpanitanon, Jirawat Saiphet, Pantita Palittapongarnpim +6
Banks are required to set aside funds in their income statement, known as a loan loss provision (LLP), to account for potential loan defaults and expenses. By treating the LLP as a…
Resistance distance distribution in large sparse random graphs
Pawat Akara-pipattana, Thiparat Chotibut, Oleg Evnin
We consider an Erdos-Renyi random graph consisting of N vertices connected by randomly and independently drawing an edge between every pair of them with probability c/N so that at…
Quantum diffusion map for nonlinear dimensionality reduction
Apimuk Sornsaeng, Ninnat Dangniam, Pantita Palittapongarnpim +1
Inspired by random walk on graphs, diffusion map (DM) is a class of unsupervised machine learning that offers automatic identification of low-dimensional data structure hidden in a…
Follow-the-Regularized-Leader Routes to Chaos in Routing Games
Jakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski +3
We study the emergence of chaotic behavior of Follow-the-Regularized Leader (FoReL) dynamics in games. We focus on the effects of increasing the population size or the scale of cos…
The birth of geometry in exponential random graphs
Pawat Akara-pipattana, Thiparat Chotibut, Oleg Evnin
Inspired by the prospect of having discretized spaces emerge from random graphs, we construct a collection of simple and explicit exponential random graph models that enjoy, in an…
Biologically Plausible Sequence Learning with Spiking Neural Networks
Zuozhu Liu, Thiparat Chotibut, Christopher Hillar +1
Motivated by the celebrated discrete-time model of nervous activity outlined by McCulloch and Pitts in 1943, we propose a novel continuous-time model, the McCulloch-Pitts network (…
Broken Detailed Balance and Non-Equilibrium Dynamics in Noisy Social Learning Models
Tushar Vaidya, Thiparat Chotibut, Georgios Piliouras
We propose new Degroot-type social learning models with feedback in a continuous time, to investigate the effect of a noisy information source on consensus formation in a social ne…
The route to chaos in routing games: When is Price of Anarchy too optimistic?
Thiparat Chotibut, Fryderyk Falniowski, Michał Misiurewicz +1
Routing games are amongst the most studied classes of games. Their two most well-known properties are that learning dynamics converge to equilibria and that all equilibria are appr…
Family of chaotic maps from game theory
Thiparat Chotibut, Fryderyk Falniowski, Michal Misiurewicz +1
From a two-agent, two-strategy congestion game where both agents apply the multiplicative weights update algorithm, we obtain a two-parameter family of maps of the unit square to i…