arXiv subjects

Lock Yue Chew

Publications and source records attributed to Lock Yue Chew.

At least 19 recordsLinked to original sources

arXiv2026

Thermoinformational State Construction: Generative Energies, Entropies, and H-Theorem Consistency

We introduce a constructive framework for assigning thermodynamic structure to an arbitrary data system from its measured microstates. Starting from an empirical distribution over configurations, we first infer a data-driven energy function by fitting a Boltzmann-type model to the observed statistics, thereby defining an energy axis that is intrinsic to the system. We then push the empirical distribution onto this energy coordinate and pose an inverse maximum-entropy problem: we learn a strictly concave trace-form entropy functional whose maximizer, under a small set of constraints extracted from the data, reproduces the observed energy-space histogram. With energy and entropy defined in this coupled, system-specific manner, macroscopic variables such as internal energy, an entropy-energy relation S(U), and a thermoinformational temperature T^(-1)= dS/dU follow consistently along admissible families of states. We demonstrate the construction on canonical unimodal and multimodal examples, including a harmonic well (recovering the classical equilibrium limit up to gauge) and a bistable double-well where global-constraint MaxEnt surrogates can obscure barrier and coexistence structure. The resulting formulation provides a principled route from microstate data to thermodynamically consistent macroscopic descriptors, with an optimized entropy matched to the empirical system.

cond-mat.stat-mech↗

arXiv2026

A variational formulation of stochastic thermodynamics: Spatially extended systems

Stochastic field theories are often constructed phenomenologically, without a systematic assessment of thermodynamic consistency or local detailed balance. This may hinder a physical description of irreversibility at the field-theoretic level beyond the standard statistical formulation of stochastic thermodynamics. Here, we develop a variational formulation for thermodynamically consistent stochastic field theories by extending Hamilton's principle of classical field theory. Introducing the second law as an axiom yields a consistent local thermodynamic structure in which novel fluctuationdissipation relations emerge naturally, ensuring local detailed balance. Remarkably, the resulting entropy production takes the same form as in standard stochastic thermodynamics, up to a reformulation in an extended phase space incorporating both configurational and thermal variables. This correspondence extends key results, including individual trajectory-level thermodynamics and fluctuation theorems. The construction is formulated within a unified geometric framework based on a generalized Lagrange-d'Alembert principle, providing a top-down connection between phenomenological modeling and thermodynamic consistency. Potential applications include thermodynamically consistent modeling of complex fluids, Lagrangian reduction by symmetry in continuum systems, and structure-preserving numerical schemes for stochastic partial differential equations.

cond-mat.stat-mech↗

arXiv2025

Variational formulation of stochastic thermodynamics: Finite-dimensional systems

In this paper, we develop a variational foundation for stochastic thermodynamics of finite-dimensional, continuous-time systems. Requiring the second law (non-negative average total entropy production) systematically yields a consistent thermodynamic structure, from which novel generalized fluctuation-dissipation relations emerge naturally, ensuring local detailed balance. This principle extends key results of stochastic thermodynamics including an individual trajectory level description of both configurational and thermal variables and fluctuation theorems in an extended thermodynamic phase space. It applies to both closed and open systems, while accommodating state-dependent parameters, nonlinear couplings between configurational and thermal degrees of freedom, and cross-correlated noise consistent with Onsager symmetry. This is achieved by establishing a unified geometric framework in which stochastic thermodynamics emerges from a generalized Lagrange-d'Alembert principle, building on the variational structure introduced by Gay-Balmaz and Yoshimura [Phil. Trans. R. Soc. A 381, 2256 (2023)]. Irreversible and stochastic forces are incorporated through nonlinear nonholonomic constraints, with entropy treated as an independent dynamical variable. This work provides a novel approach for thermodynamically consistent modeling of stochastic systems, and paves the way to applications in continuum systems such as active and complex fluids.

cond-mat.stat-mech↗

arXiv2024

Quantum-inspired identification of complex cellular automata

Elementary cellular automata (ECA) present iconic examples of complex systems. Though described only by one-dimensional strings of binary cells evolving according to nearest-neighbour update rules, certain ECA rules manifest complex dynamics capable of universal computation. Yet, the classification of precisely which rules exhibit complex behaviour remains a significant challenge. Here we approach this question using tools from quantum stochastic modelling, where quantum statistical memory -- the memory required to model a stochastic process using a class of quantum machines -- can be used to quantify the structure of a stochastic process. By viewing ECA rules as transformations of stochastic patterns, we ask: Does an ECA generate structure as quantified by the quantum statistical memory, and if so, how quickly? We illustrate how the growth of this measure over time correctly distinguishes simple ECA from complex counterparts. Moreover, it provides a more refined means for quantitatively identifying complex ECAs -- providing a spectrum on which we can rank the complexity of ECA by the rate in which they generate structure.

quant-ph↗

arXiv2024

Signs of criticality in social explosions

The success of an on-line movement could be defined in terms of the shift to large-scale and the later off-line massive street actions of protests. The role of social media in this process is to facilitate the transformation from small or local feelings of disagreement into large-scale social actions. The way how social media achieves that effect is by growing clusters of people and groups with similar effervescent feelings, which in another case would never be in communication. It is natural to think that these kinds of macro social actions, as a consequence of the spontaneous and massive interactions, will attain the growth and divergence of the correlation length, giving rise to important simplifications on several statistics. In this work, we report the presence of signs of criticality in social demonstrations. Namely, the same power-law exponents are found whenever the distributions are calculated, either considering the same windows-time or the same number of hashtags. The exponents for the distributions during the event were found to be smaller than before (and after) the event. The latter also happens whenever the hashtags are counted only once per user or if all their usages are considered. By means of network representations, we show that the systems present two kinds of high correlations, characterised by either high or low values of modularity. The temporal points of high modularity are characterised by a sustained correlation while the ones of low modularity are characterised by a punctual correlation. The importance of analysing systems near a critical point is that any small disturbance can escalate and induce large-scale -- nationwide -- chain reactions.

physics.soc-ph↗

arXiv2022

Inferring origin-destination distribution of agent transfer in a complex network using deep gated recurrent units

Predicting the origin-destination (OD) probability distribution of agent transfer is an important problem for managing complex systems. However, prediction accuracy of associated statistical estimators suffer from underdetermination. While specific techniques have been proposed to overcome this deficiency, there still lacks a general approach. Here, we propose a deep neural network framework with gated recurrent units (DNNGRU) to address this gap. Our DNNGRU is \emph{network-free}, as it is trained by supervised learning with time-series data on the volume of agents passing through edges. We use it to investigate how network topologies affect OD prediction accuracy, where performance enhancement is observed to depend on the degree of overlap between paths taken by different ODs. By comparing against methods that give exact results, we demonstrate the near-optimal performance of our DNNGRU, which we found to consistently outperform existing methods and alternative neural network architectures, under diverse data generation scenarios.

physics.soc-ph↗

arXiv2022

Jacobian Granger Causal Neural Networks for Analysis of Stationary and Nonstationary Data

Granger causality is a commonly used method for uncovering information flow and dependencies in a time series. Here we introduce JGC (Jacobian Granger Causality), a neural network-based approach to Granger causality using the Jacobian as a measure of variable importance, and propose a thresholding procedure for inferring Granger causal variables using this measure. The resulting approach performs consistently well compared to other approaches in identifying Granger causal variables, the associated time lags, as well as interaction signs. Lastly, through the inclusion of a time variable, we show that this approach is able to learn the temporal dependencies for nonstationary systems whose Granger causal structures change in time.

cs.LG↗

arXiv2022

Can bus bunching reduce waiting time?

Bus bunching is ostensibly regarded as a detrimental phenomenon in bus systems. We study a bus loop with two bus stops, one regular and one spike bus stop, where bunched buses can outperform staggered buses. The spike bus stop models a bus stop connected to a train or metro service, where passengers arrive in groups at periodic intervals (spikes). We introduce the configuration of synchronised bunched buses, where bunched buses wait for the spike in demand. For a wide range of parameters, synchronised bunched buses outperform perfectly staggered buses in terms of minimising the waiting time of commuters. We present an analytical formulation of the average waiting time in the case of bunched buses, synchronised bunched buses and perfectly staggered buses with the consideration of different passenger demand, number of buses, and bus capacity. We demonstrate the validity of our analytical results through an agent-based simulation of the bus loop system.

physics.soc-ph↗

arXiv2021

Bali's ancient rice terraces: A Hamiltonian approach

We propose a Hamiltonian approach to reproduce the relevant elements of the centuries-old Subak irrigation system in Bali, showing a cluster-size power-law distribution. The resulting system presents two equilibria. The first balance is between energy and entropy contributions. The second lies in the energy contribution: a local Potts-type interaction and a long-range anti-ferromagnetic one without attenuation. Finite-size scaling analysis shows that as a result of the second balance, the transition balancing energy and entropy contributions for low values of the antiferromagnetic contribution is absorbed by the transition for high values of that contribution as the system size increases. The system thus presents only a weak-first order phase transition at the thermodynamic limit. This extends the Hamiltonian framework to a new domain of coupled human-environmental interactions.

cond-mat.stat-mech↗

arXiv2021

Bunching Dynamics of Buses in a Loop

Bus bunching is a curse of transportation systems such as buses in a loop. Here we present an analytical method to find the number of revolutions before two buses bunch in an idealised system, as a function of the initial distance and the crowdedness of the bus stops. We can also characterise the average waiting time for passengers as the buses bunch. The results give a better understanding of the phenomenon of bus bunching and design recommendations for bus loops.

cond-mat.stat-mech↗

arXiv2021

Chaotic semi-express buses in a loop

Urban mobility involves many interacting components: buses, cars, commuters, pedestrians, trains etc., making it a very complex system to study. Even a bus system responsible for delivering commuters from their origins to their destinations in a loop service already exhibits very complicated dynamics. Here, we investigate the dynamics of a simplified version of such a bus loop system consisting of two buses serving three bus stops. Specifically, we consider a configuration of one bus operating as a normal bus which picks up passengers from bus stops $A$ and $B$, and then delivers them to bus stop $C$, whilst the second bus acts as an express bus which picks up passengers only from bus stop $B$ and then delivers them to bus stop $C$. The two buses are like asymmetric agents coupled to bus stop $B$ as they interact via picking up passengers from this common bus stop. Intriguingly, this \emph{semi-express} bus configuration is more efficient and has a lower average waiting time for buses, compared to a configuration of two normal buses or a configuration of two express buses. We reckon the efficiency arises from the chaotic dynamics exhibited in the semi-express system, where the tendency towards anti-bunching is greater than that towards bunching, in contradistinction to the regular bunching behavior of two normal buses or the independent periodic behaviour of two non-interacting express buses.

physics.soc-ph↗

arXiv2021

Optimal assignment of buses to bus stops in a loop by reinforcement learning

Bus systems involve complex bus-bus and bus-passengers interactions. We study the problem of assigning buses to bus stops to minimise the average waiting time of passengers, W. An analytical theory for two specific cases of interactions is formulated: normal situation where all buses board passengers from every bus stop, versus novel express buses where disjoint subsets of non-interacting buses serve disjoint subsets of bus stops. Our formulation allows exact calculation of W for general loops in the two cases examined. Compared with regular buses, we present scenarios where express buses show improvement in W. Useful insights are obtained from our theory: 1) there is a minimum number of buses needed, 2) splitting a crowded bus stop into two less crowded ones always increases W for regular buses, 3) changing the destination of passengers and location of bus stops do not influence W. In the second part, we introduce a reinforcement-learning platform that overcomes limitations of our analytical method to search for better allocations of buses to bus stops that minimise W. Compared with the previous cases, any possible interaction between buses is allowed, unlocking novel emergent strategies. We apply this tool to a simple toy model and three empirically-motivated bus loops, based on data collected from the Nanyang Technological University shuttle bus system. In the simplified model, we observe an unexpected strategy emerging that could not be analysed with our mathematical formulation and displays chaotic behaviour. The possible configurations in the three empirically-motivated scenarios are approximately 10^11, 10^11 and 10^20, so a brute-force approach is impossible. Our algorithm reduces W by 12% to 32% compared with regular buses and 12% to 29% compared with express buses. This tool has practical applications because it works independently of the specific characteristics of a bus loop.

physics.soc-ph↗

arXiv2020

No-boarding buses: Synchronisation for efficiency

We investigate a no-boarding policy in a system of $N$ buses serving $M$ bus stops in a loop, which is an entrainment mechanism to keep buses synchronised in a reasonably staggered configuration. Buses always allow alighting, but would disallow boarding if certain criteria are met. For an analytically tractable theory, buses move with the same natural speed (applicable to programmable self-driving buses), where the average waiting time experienced by passengers waiting at the bus stop for a bus to arrive can be calculated. The analytical results show that a no-boarding policy can dramatically reduce the average waiting time, as compared to the usual situation without the no-boarding policy. Subsequently, we carry out simulations to verify these theoretical analyses, also extending the simulations to typical human-driven buses with different natural speeds based on real data. Finally, a simple general adaptive algorithm is implemented to dynamically determine when to implement no-boarding in a simulation for a real university shuttle bus service.

physics.soc-ph↗

arXiv2020

Analysis and simulation of intervention strategies against bus bunching by means of an empirical agent-based model

In this paper, we propose an Empirically-based Monte Carlo Bus-network (EMB) model as a test bed to simulate intervention strategies to overcome the inefficiencies of bus bunching. The EMB model is an agent-based model which utilizes the positional and temporal data of the buses obtained from the Global Positioning System (GPS) to constitute: (1) a set of empirical velocity distributions of the buses, and (2) a set of exponential distributions of inter-arrival time of passengers at the bus stops. Monte Carlo sampling is then performed on these two derived probability distributions to yield the stochastic dynamics of both the buses' motion and passengers' arrival. Our EMB model is generic and can be applied to any real-world bus network system. In particular, we have validated the model against the Nanyang Technological University's Shuttle Bus System by demonstrating its accuracy in capturing the bunching dynamics of the shuttle buses. Furthermore, we have analyzed the efficacy of three intervention strategies: holding, no-boarding, and centralized-pulsing, against bus bunching by incorporating the rule-set of these strategies into the model. Under the scenario where the buses have the same velocity, we found that all three strategies improve both the waiting and travelling time of the commuters. However, when the buses have different velocities, only the centralized-pulsing scheme consistently outperform the control scenario where the buses periodically bunch together.

physics.soc-ph↗

arXiv2019

Stability of anti-bunched buses and local unidirectional Kuramoto oscillators

Inspired by our recent work that relates bus bunching as a phenomenon of synchronisation of phase oscillators, we construct a model of Kuramoto oscillators that follows an analogous interaction mechanism of local unidirectional coupling. In the bus loop system, we can introduce a no-boarding policy as a form of kicking force to achieve a stable staggered (anti-bunched) state. For Kuramoto oscillators, it turns out that such stable anti-bunched states can exist (without any additional kicking force) if the number of oscillators are at least five. This correspondence between the bus loop system and the local unidirectional Kuramoto oscillators leads to the insight on how the bus loop system can remain staggered.

nlin.AO↗

arXiv2019

Intelligent buses in a loop service: Emergence of no-boarding and holding strategies

We study how $N$ intelligent buses serving a loop of $M$ bus stops learn a \emph{no-boarding strategy} and a \emph{holding strategy} by reinforcement learning. The high level no-boarding and holding strategies emerge from the low level actions of \emph{stay} or \emph{leave} when a bus is at a bus stop and everyone who wishes to alight has done so. A reward that encourages the buses to strive towards a staggered phase difference amongst them whilst picking up people allows the reinforcement learning process to converge to an optimal Q-table within a reasonable amount of simulation time. It is remarkable that this emergent behaviour of intelligent buses turns out to minimise the average waiting time of commuters, in various setups where buses have identical natural frequency, or different natural frequencies during busy as well as lull periods. Cooperative actions are also observed, e.g. the buses learn to \emph{unbunch}.

physics.soc-ph↗

arXiv2019

No-boarding buses: Agents allowed to cooperate or defect

We study a bus system with a no-boarding policy, where a "slow" bus may disallow passengers from boarding if it meets some criteria. When the no-boarding policy is activated, people waiting to board at the bus stop are given the choices of \emph{cooperating} or \emph{defecting}. The people's heterogeneous behaviours are modelled by inductive reasoning and bounded rationality, inspired by the El Farol problem and the minority game. In defecting the no-boarding policy, instead of the minority group being the winning group, we investigate several scenarios where defectors win if the number of defectors does not exceed the maximum number of allowed defectors but lose otherwise. Contrary to the classical minority game which has $N$ agents repeatedly playing amongst themselves, many real-world situations like boarding a bus involves only a subset of agents who "play each round", with \emph{different subsets playing at different rounds}. We find for such realistic situations, there is no phase transition with no herding behaviour when the usual control paramater $2^m/N$ is small. The absence of the herding behaviour assures feasible and sustainable implementation of the no-boarding policy with allowance for defections, without leading to bus bunching.

physics.soc-ph↗

arXiv2019

Bus bunching as a synchronisation phenomenon

Bus bunching is a perennial phenomenon that not only diminishes the efficiency of a bus system, but also prevents transit authorities from keeping buses on schedule. We present a physical theory of buses serving a loop of bus stops as a ring of coupled self-oscillators, analogous to the Kuramoto model. Sustained bunching is a repercussion of the process of phase synchronisation whereby the phases of the oscillators are locked to each other. This emerges when demand exceeds a critical threshold. Buses also bunch at low demand, albeit temporarily, due to frequency detuning arising from different human drivers' distinct natural speeds. We calculate the critical transition when \emph{complete phase locking} (full synchronisation) occurs for the bus system, and posit the critical transition to \emph{completely no phase locking} (zero synchronisation). The intermediate regime is the phase where clusters of partially phase locked buses exist. Intriguingly, these theoretical results are in close correspondence to real buses in a university's shuttle bus system.

physics.soc-ph↗