Eroğlu, Deniz
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Deniz, Eroglu
Eroglu,D.
Eroğlu, DENIZ
DENIZ EROĞLU
Eroglu, Deniz
Eroglu D.
EROĞLU, DENIZ
Eroğlu,D.
Deniz EROĞLU
Eroğlu, D.
Eroğlu, Deniz
Deniz Eroğlu
E., Deniz
EROĞLU, Deniz
E.,Deniz
D. Eroğlu
Eroglu,Deniz
Eroğlu, Deniz
Eroglu,D.
Eroğlu, DENIZ
DENIZ EROĞLU
Eroglu, Deniz
Eroglu D.
EROĞLU, DENIZ
Eroğlu,D.
Deniz EROĞLU
Eroğlu, D.
Eroğlu, Deniz
Deniz Eroğlu
E., Deniz
EROĞLU, Deniz
E.,Deniz
D. Eroğlu
Eroglu,Deniz
Eroğlu, Deniz
Job Title
Dr. Öğr. Üyesi
Email Address
Main Affiliation
Molecular Biology and Genetics
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
11
SUSTAINABLE CITIES AND COMMUNITIES
3
Research Products
17
PARTNERSHIPS FOR THE GOALS
1
Research Products
14
LIFE BELOW WATER
1
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
15
LIFE ON LAND
0
Research Products
1
NO POVERTY
0
Research Products
7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
6
CLEAN WATER AND SANITATION
0
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
3
GOOD HEALTH AND WELL-BEING
2
Research Products
2
ZERO HUNGER
0
Research Products
4
QUALITY EDUCATION
0
Research Products
10
REDUCED INEQUALITIES
0
Research Products
13
CLIMATE ACTION
1
Research Products
5
GENDER EQUALITY
0
Research Products
Documents
36
Citations
731
h-index
16
This researcher does not have a WoS ID.
Scholarly Output
27
Articles
21
Views / Downloads
262/2283
Supervised MSc Theses
3
Supervised PhD Theses
3
WoS Citation Count
201
Scopus Citation Count
219
WoS h-index
8
Scopus h-index
8
Patents
0
Projects
0
WoS Citations per Publication
7.44
Scopus Citations per Publication
8.11
Open Access Source
20
Supervised Theses
6
| Journal | Count |
|---|---|
| Physical Review Research | 2 |
| Physical Review X | 2 |
| Earth Surface Processes and Landforms | 1 |
| Entropy | 1 |
| European Physical Journal-Special Topics | 1 |
Current Page: 1 / 4
Scopus Quartile Distribution
Competency Cloud
27 results
Scholarly Output Search Results
Now showing 1 - 10 of 27
Article Citation - WoS: 29Citation - Scopus: 27Network Structural Origin of Instabilities in Large Complex Systems(Amer Assoc Advancement Science, 2022) Duan, Chao; Nishikawa, Takashi; Eroglu, Deniz; Motter, Adilson E.A central issue in the study of large complex network systems, such as power grids, financial networks, and ecological systems, is to understand their response to dynamical perturbations. Recent studies recognize that many real networks show nonnormality and that nonnormality can give rise to reactivity-the capacity of a linearly stable system to amplify its response to perturbations, oftentimes exciting nonlinear instabilities. Here, we identify network structural properties underlying the pervasiveness of nonnormality and reactivity in real directed networks, which we establish using the most extensive dataset of such networks studied in this context to date. The identified properties are imbalances between incoming and outgoing network links and paths at each node. On the basis of this characterization, we develop a theory that quantitatively predicts nonnormality and reactivity and explains the observed pervasiveness. We suggest that these results can be used to design, upgrade, control, and manage networks to avoid or promote network instabilities.Article Citation - WoS: 4Citation - Scopus: 4First-Principle Validation of Fourier's Law in D=1, 2, 3 Classical Systems(Elsevier, 2023) Tsallis, Constantino; Lima, Henrique Santos; Tirnakli, Ugur; Eroglu, DenizWe numerically study the thermal transport in the classical inertial nearest-neighbor XY ferromagnet in d = 1, 2, 3, the total number of sites being given by N = Ld, where L is the linear size of the system. For the thermal conductance sigma, we obtain sigma(T, L)L delta(d)= A(d) e-B(d) [L gamma (d)T ]eta(d) (with ez q(d) q equivalent to [1+(1-q)z]1/(1-q); ez1 = ez; A(d) > 0; B(d) > 0; q(d) > 1; eta(d) > 2; delta >= 0; gamma(d) > 0), for all values of L gamma(d)T for d = 1, 2, 3. In the L -> infinity limit, we have sigma proportional to 1/L rho sigma(d) with rho sigma(d) = delta(d)+gamma(d)eta(d)/[q(d)-1]. The material conductivity is given by kappa = sigma Ld proportional to 1/L rho kappa(d) (L -> infinity) with rho kappa(d) = rho sigma(d) - d. Our numerical results are consistent with 'conspiratory' d-dependences of (q, eta, delta, gamma), which comply with normal thermal conductivity (Fourier law) for all dimensions.(c) 2023 Published by Elsevier B.V.Article Citation - WoS: 4Citation - Scopus: 7Collective dynamics of random Janus oscillator networks(AMER PHYSICAL SOC, 2020) Peron, Thomas; Eroğlu, Deniz; Rodrigues, Francisco A.; Moreno, YamirJanus oscillators have been recently introduced as a remarkably simple phase oscillator model that exhibits nontrivial dynamical patterns-such as chimeras, explosive transitions, and asymmetry-induced synchronization-that were once observed only in specifically tailored models. Here we study ensembles of Janus oscillators coupled on large homogeneous and heterogeneous networks. By virtue of the Ott-Antonsen reduction scheme, we find that the rich dynamics of Janus oscillators persists in the thermodynamic limit of random regular, Erdos-Renyi, and scale-free random networks. We uncover for all these networks the coexistence between partially synchronized states and a multitude of solutions of a collective state we denominate as a breathing standing wave, which displays global oscillations. Furthermore, abrupt transitions of the global and local order parameters are observed for all topologies considered. Interestingly, only for scale-free networks, it is found that states displaying global oscillations vanish in the thermodynamic limit.Article Citation - WoS: 19Citation - Scopus: 20Recurrence analysis of extreme event-like data(COPERNICUS GESELLSCHAFT MBH, 2021) Banerjee, Abhirup; Goswami, Bedartha; Hirata, Yoshito; Eroğlu, Deniz; Merz, Bruno; Kurths, Juergen; Marwan, NorbertThe identification of recurrences at various time-scales in extreme event-like time series is challenging because of the rare occurrence of events which are separated by large temporal gaps. Most of the existing time series analysis techniques cannot be used to analyze an extreme event-like time series in its unaltered form. The study of the system dynamics by reconstruction of the phase space using the standard delay embedding method is not directly applicable to event-like time series as it assumes a Euclidean notion of distance between states in the phase space. The edit distance method is a novel approach that uses the point-process nature of events. We propose a modification of edit distance to analyze the dynamics of extreme event-like time series by incorporating a nonlinear function which takes into account the sparse distribution of extreme events and utilizes the physical significance of their temporal pattern. We apply the modified edit distance method to event-like data generated from point process as well as flood event series constructed from discharge data of the Mississippi River in the USA and compute their recurrence plots. From the recurrence analysis, we are able to quantify the deterministic properties of extreme event-like data. We also show that there is a significant serial dependency in the flood time series by using the random shuffle surrogate method.Article Citation - WoS: 6Citation - Scopus: 6Transformation Cost Spectrum for Irregularly Sampled Time Series(Springer Heidelberg, 2023) Ozdes, Celik; Eroglu, DenizIrregularly sampled time series analysis is a common problem in various disciplines. Since conventional methods are not directly applicable to irregularly sampled time series, a common interpolation approach is used; however, this causes data distortion and consequently biases further analyses. We propose a method that yields a regularly sampled time series spectrum of costs with minimum information loss. Each time series in this spectrum is a stationary series and acts as a difference filter. The transformation costs approach derives the differences between consecutive and arbitrarily sized segments. After obtaining regular sampling, recurrence plot analysis is performed to distinguish regime transitions. The approach is applied to a prototypical model to validate its performance and to different palaeoclimate proxy data sets located around Africa to identify critical climate transition periods during the last 5 million years and their characteristic properties.Doctoral Thesis Network Reconstruction From Data(Kadir Has Üniversitesi, 2023) Kement, İrem Topal; Eroğlu, DenizGüç şebekeleri, ekosistem, iklim, nöron ağları ve bir hastalığın küresel ölçekte yayılması gibi hayatımızın temel bileşenlerinin bir ortak noktası vardır: karmaşık ağlar üzerinde etkileşen dinamik birimler olarak modellenebilmeleri. Pek çok örnekte, karmaşık sistemlerden elde edilen veriler doğal bir ağ yapısını temsil eder veya sistem özünde ağ yapısında olmasa bile bir ağ gibi modellenebilir. Ağ dinamiğini bilmek, bu karmaşık sistemlerden istenen işlevselliği elde etmek, dolayısıyla gelecekteki durumunu tahmin etmek ve kontrol etmek için çok önemlidir. Örneğin beynimizdeki nöron ağlarının etkileşimindeki normal olmayan değişiklikler patolojik durumlara yol açabileceğinden, bu ağlar insan sağlığı için önemli bir dinamik ağ sınıfını oluştururlar. Epilepsi krizleri nöron ağlarının etkileşimlerinin değişmesi ile beliren ağ senkronizasyonu ile ilişkilidir. Bu tip istenmeyen nöronal senkronizasyona kritik geçişleri önceden tahmin etmek ve erken uyarı sinyallerini tespit edecek teknolojileri icat etmek hayati önem taşır. Nöronların iç dinamikleri ve aralarındaki bağlantı şemasından oluşan nöron ağlarında, senkronizasyona kritik geçiş doğrudan belirlenemez. Bu nedenle amaç, parametre değişikliklerinden kaynaklanan kritik geçişleri tahmin etmek için ağ dinamiğinin denklemini her bir düğümden elde edilen ölçüm verisinden öğrenmektir. Bu doktora çalışması, dinamik sistemler teorisinden ortalama alan yaklaşımlarını istatistiksel öğrenme araçlarıyla birleştirerek zaman serisi gözlemlerinden dinamik bir ağı yeniden yapılandırma yaklaşımı sunar. Önerilen veri güdümlü yeniden yapılandırma yaklaşımı iki temel varsayımda bulunur: sinirbilimsel bir model ve tüm düğümlerin verisine tam erişim. Buna karşılık, düğümlerin iç dinamikleri, aralarındaki bağlantı yapısı ve etkileşim şekli bilinmez. Sinirbilimsel koşullar, nöronların iç dinamiğinin kaotik davranış göstermesi, zayıf bir etkileşimde olmaları ve ölçekten bağımsız bir ağ ile temsil edilmeleri olarak sıralanır. Metodolojimiz tüm bilinmeyenleri nispeten kısa zaman serileri kullanarak doğru bir şekilde öğrenir ve ağ boyutundan bağımsızdır. Kısa süreli ölçüm ve büyük ağlarda başarı gerçek dünya örneklerine yaklaşabilmemiz için önemli iki kısıt olarak ele alınmıştır. Sonuç olarak, veriden öğrenilmiş ağ modeli tüm parametreleri kontrol edebilmemize ve karmaşık ağın kolektif davranışını tahmin edebilmemize izin verir.Article Forecasting Critical Economic & Political Events Via Electricity Consumption Patterns in the United States of America and Turkey(Springernature, 2025) Ozdes, Celik; Ediger, Volkan S.; Eroglu, DenizImpacts from natural disasters, government decisions and public's reactions can significantly alter societal daily routines. These effects resonate in systems where individual contributions, such as energy consumption, serve as indirect indicators of societal welfare and living standards. Preparedness for unforeseen events is crucial to enhancing societal well-being. Thus, analysing historical data for unexpected critical transitions and forecasting future occurrences is paramount. Recurrence properties of gross monthly electricity consumption in the United States of America and Turkey are examined, revealing coinciding critical periods with extreme regimes identified by a determinism time series. An ensemble of neural network proxies is then employed to forecast critical periods within a limited time frame, enabling the anticipation of similar occurrences. Validation of this approach demonstrates high predictive performance when measured quantities adequately reflect underlying system dynamics. Predictions based on electricity consumption data suggest potential systemic and socioeconomic crises for both nations within one year, with probabilities, 85% for the US and 32% for Turkey.Master Thesis The Effect of Link Modifications on Network Synchronization(Kadir Has Üniversitesi, 2022) KIRAN, NARÇİÇEĞİ; Eroglu, DenizA major issue in studying complex network systems, such as neuroscience and power grids, is understanding the response of network dynamics to link modifications. The notion of network G(G, f, H) refers to di↵usively coupled identical oscillators, where isolated dynamics are chosen to be chaotic. As a consequence of the di↵usive nature, a globally synchronized state emerges as an invariant synchronization subspace, and it will be locally stable above critical coupling strength. Furthermore, the real part of the second minimum eigenvalue of the Laplacian matrix is inverse proportional to the critical coupling strength. Thus, we can use it to determine the synchronizability between two networks. Due to the asymmetry of the Laplacian matrix of a directed graph, adding directed links might cause a decrease in the real part of the second minimum eigenvalue of the Laplacian. If, after adding a link to a graph in a given network, the real part of the second minimum eigenvalue of the Laplacian matrix increases, it is called the enhancement of synchronization. Otherwise, it is called the hindrance of synchronization. In this research, we explore how the stability of synchronization at di↵usively coupled oscillators is a↵ected by link modifications for the networks created using particular motifs, i.e., cycle and star motifs. We consider a weakly connected directed graph consisting of two strongly connected components connected by directed link(s) (called cutset). We study the synchronization transitions in such networks when new directed link(s) between the components, in the opposite direction of the cutset, is added and strongly connects the whole network. We explore which properties of underlying graphs and their connected components may hinder or enhance the synchronization.Article Fourier's Law Breakdown for the Planar-Rotor Chain with Long-Range Interactions(Elsevier, 2026) Lima, Henrique Santos; Tsallis, Constantino; Eroglu, Deniz; Tirnakli, UgurFourier's law, which linearly relates heat flux to the negative gradient of temperature, is a fundamental principle in thermal physics and widely applied across materials science and engineering. However, its validity in low-dimensional systems with long-range interactions remains only partially understood. We investigate here the thermal transport along a onedimensional chain of classical planar rotators with algebraically decaying interactions 1/ with distance ( >= 0), known as the inertial a-XY model. Using nonequilibrium simulations with thermal reservoirs at the boundaries, we numerically study the thermal conductance as a function of system sizea, temperature , and . We find that the results obey a universal scaling law characterized by a stretched-exponential function with -dependent parameters. Notably, a threshold at approximate to 2 separates two regimes: for >= , Fourier's law holds with size-independent conductivity = , while for < , anomalous transport is observed, corroborating (with higher precision) the results reported in Phys.Rev.E94,042117(2016). These findings provide a quantitative framework for understanding the breakdown of Fourier's law in systems with long-range interactions. The simulation is carried out by assuming the equations of motion, which include Langevin heat baths applied to the first and last particles, and are integrated using the Velocity Verlet algorithm. The conductance is calculated from the connection between Lagrangian heat flux and heat equation for typical values of (, , ). For large , the results can be collapsed into an universal -stretched exponential form, namely proportional to -() , where = [1 + (1-)]1/(1-). The parameters (, , ,) are -dependent, and is the index of the -stretched exponential. This form is achievable due to the ratio /( - 1) being almost constant with respect to the lattice size. These findings provide significant insights into heat conduction mechanisms in systems with long-range interactions.Article Data-Driven Modeling of Traffic Flow in Macroscopic Network Systems(AIP Publishing, 2025) Firat, Toprak; Eroglu, DenizUrban traffic modeling is essential for understanding and mitigating congestion, yet existing approaches face a trade-off between realism and scalability. Microscopic agent-based simulators capture individual vehicle behavior but are computationally intensive and hard to calibrate at scale. Macroscopic models, while more efficient, often rely on strong assumptions, such as fixed origin-destination flows, or oversimplify network dynamics. In this work, we propose a data-driven macroscopic model that simulates traffic as a discrete-time load-exchange process over flow networks. The model captures key phenomena such as bottlenecks, spillbacks, and adaptive load redistribution using only road-type attributes, network structure, and observed traffic density. Parameter learning is performed via evolutionary optimization, allowing the model to adapt to both synthetic and real-world conditions without assuming latent travel demand. We evaluate the framework on synthetic grid-like networks and on real traffic data from London, Istanbul, and New York. The resulting framework provides a scalable and interpretable alternative for urban traffic forecasting, balancing predictive accuracy with computational efficiency across diverse network conditions.
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