Improvement in the survival rate of gastric cancer, a prevalent global malignancy and the leading... more Improvement in the survival rate of gastric cancer, a prevalent global malignancy and the leading cause of cancer-related mortality calls for more avenues in molecular therapy. This work aims to comprehend drug resistance and exploration of multiple-drug combinations for enhanced therapeutic treatment. An endogenous network modeling clinic data with core gastric cancer molecules, functional modules and pathways is constructed, which is then transformed into dynamics equations for in-silicon studies. Principal component analysis, hierarchical clustering, and K-means clustering are utilized to map the attractor domains of the stochastic model to the normal and pathological phenotypes identified from the clinical data. The analyses demonstrate gastric cancer as a cluster of stable states emerging within the stochastic dynamics and elucidate the cause of resistance to anti-VEGF monotherapy in cancer treatment as the limitation of single pathway in preventing the cancer progression. The feasibility of multiple objectives of therapy targeting specified molecules and/or pathways is explored. This study verifies the rationality of the platform of endogenous network modeling, which contributes to the development of cross-functional multitarget combinations in clinical trials.
Despite numerous recent studies on the Hall anomaly following the discovery of cuprate supercondu... more Despite numerous recent studies on the Hall anomaly following the discovery of cuprate superconductivity, the origin of this phenomenon remains contentious. We demonstrate that a previously proposed mechanism, in which vacancy-on-fragment of the flux-line crystal, provides an alternative explanation for the observations of Bi 2 Sr 2 CaCu 2 O x thin films made by Nitzav and Kanigel [Phys. Rev. B. 107, 094516 (2023)], without the need for adjustable parameters. Specifically, we show that the power-law behavior of ρ xy over ρ xx , with and without sign reversal, is consistent with the picture of vacancies versus fragments. Interestingly, we find that the effective length of vortex lines is consistently 1.5 unit cells (UC) across different experiments, independent of film thickness.
Bulletin of the American Physical Society, Mar 3, 2020
We uncover a novel phenomenon from a recent artificial light-harvesting experiment [P.-Z. Chen et... more We uncover a novel phenomenon from a recent artificial light-harvesting experiment [P.-Z. Chen et al., Angew. Chem., Int. Ed. Engl. 55, 2759 (2016)] on organic nanocrystals of self-assembled difluoroboron chromophores. A resonant confinement of a polariton under strong photon-exciton coupling is predicted to exist within the microcavity of the crystal's own natural boundaries. Moreover, the radiative energy of a localized exciton falls into the spectrum of confinement. Hence, in the experiment, the spontaneous emission of an excited pigment would undergo a two-step process. It should first decay to an excitonic polariton trapped by the cavity resonance. The intermediate polariton could then funnel the energy directly to a doped acceptor, leading to the over 90% transfer efficiency observed at less than 1=1000 acceptor=donor ratio. The proposed mechanism is supported by parameter-free analyses entirely based on experiment data. Our finding may imply possible polariton-mediated pathways for energy transfers in biological photosynthesis.
Stochastic gradient descent (SGD), a widely used algorithm in deep-learning neural networks has a... more Stochastic gradient descent (SGD), a widely used algorithm in deep-learning neural networks has attracted continuing studies for the theoretical principles behind its success. A recent work reports an anomaly (inverse) relation between the variance of neural weights and the landscape flatness of the loss function driven under SGD [Feng & Tu, PNAS 118, 0027 (2021)]. To investigate this seemingly violation of statistical physics principle, the properties of SGD near fixed points are analysed via a dynamic decomposition method. Our approach recovers the true "energy" function under which the universal Boltzmann distribution holds. It differs from the cost function in general and resolves the paradox raised by the the anomaly. The study bridges the gap between the classical statistical mechanics and the emerging discipline of artificial intelligence, with potential for better algorithms to the latter.
Quantum computing is a new way to processing quantum information by using superposition and entan... more Quantum computing is a new way to processing quantum information by using superposition and entanglement of the quantum system. Quantum state's vast Hilbert space allows it to perform operations that classical computers cannot compared with classical computing, quantum computing has unique advantages in dealing with some complex problems, so it has attracted wide attention. Computing a single qubit is the first of seven fundamental stages needed to achieve a large-scale quantum computer that is universal, scalable and fault-tolerant. In other words, the primary task of quantum computing is the careful preparation and precise regulation of qubits. At present, the physical systems that can be used as qubits include superconducting qubits, semiconductor qubits, ion trap systems and nitrogen-vacancy (NV) color centers, etc. These physical systems have made great progress in terms of decoherence time and scalability. Due to the vulnerability of qubits, ambient thermal noise can cause...
Stochastic gradient descent (SGD), a widely used algorithm in deep-learning neural networks has a... more Stochastic gradient descent (SGD), a widely used algorithm in deep-learning neural networks has attracted continuing studies for the theoretical principles behind its success. A recent work reports an anomaly (inverse) relation between the variance of neural weights and the landscape flatness of the loss function driven under SGD [Feng & Tu, PNAS 118, 0027 (2021)]. To investigate this seemingly violation of statistical physics principle, the properties of SGD near fixed points are analysed via a dynamic decomposition method. Our approach recovers the true "energy" function under which the universal Boltzmann distribution holds. It differs from the cost function in general and resolves the paradox raised by the the anomaly. The study bridges the gap between the classical statistical mechanics and the emerging discipline of artificial intelligence, with potential for better algorithms to the latter.
Hall anomaly, as appears in the mixed-state Hall resistivity of type-II superconductors, has had ... more Hall anomaly, as appears in the mixed-state Hall resistivity of type-II superconductors, has had numerous theories but yet a consensus on its origin. In this work, we conducted a quantitative analysis of the magnetotransport measurements on BSCCO thin films by Zhao et al. [Phys. Rev. Lett. 122, 247001 (2019)] and validate a previously proposed vacancy mechanism [cf. J. Phys. Condens. Matter. 10, L677 (1998)] with many-body vortex correlations for the phenomenon. The model attributes the Hall anomaly to the motion of vacancies in pinned fragments of vortex lattice. Its validity is first examined by an exploration on the vortex states near the Kosterlitz-Thouless transition on the vortex crystal. Comparisons are then carried out between the measured activation energies with the calculated creation energy of the vortex-anti-vortex pair and the vacancy energy on the flux-line lattice, with no adjustable parameter. Our analysis elucidates the theoretical basis and prerequisites of the vacancy model. In particular, the vacancy activation energies are an order of magnitude smaller than that of a sole vortex line. The proposed mechanism may provide a macro-theoretical framework for other studies.
The production of secondary metabolites, while important for bioengineering purposes, presents a ... more The production of secondary metabolites, while important for bioengineering purposes, presents a paradox in itself. Though widely existing in plants and bacteria, they have no definite physiological roles. Yet in both native habitats and laboratories, their production appears robust and follows apparent metabolic switches. We show in this work that the enzyme-catalysed process may improve the metabolic stability of the cells. The latter can be responsible for the overall metabolic behaviours such as dynamic metabolic landscape, metabolic switches and robustness, which can in turn affect the genetic formation of the organism in question. Mangrove-derived <i>Streptomyces xiamenensis</i> 318, with a relatively compact genome for secondary metabolism, is used as a model organism in our investigation. Integrated studies via kinetic metabolic modelling, transcriptase measurements and metabolic profiling were performed on this strain. Our results demonstrate that the secondary ...
Quantum dynamics of a particle coupled to a fermionic environment is considered, with particular ... more Quantum dynamics of a particle coupled to a fermionic environment is considered, with particular emphasis on the formulation of macroscopic quantum phenomena. The framework is based on a path integral formalism for the realtime density matrix. After integrating out of the fermion variables of the environment, we embed the whole environmental effects on the particle into the so-called influence functional in analogy to Feynman and Vernon's initial work. We then show that to the second order of the coupling constant, the exponent of the influence functional is in exact agreement with that due to a linear dissipative environment (boson bath). Having obtained this, we turn to a specific model in which the influence functional can be exactly evaluated in a long-time limit (long compared to the inverse of the cutoff frequency of the environmental spectrum). In this circumstance, we mainly address our attention to the quantum mechanical representation of the system-plus-environment from the known classical properties of the particle. It is shown that, in particular, the equivalence between the fermion bath and the boson bath is generally correct for a singlechannel coupling provided we make a simple mapping between the nonlinear interaction functions of the baths. Finally, generalizations of the model to more complicated situations are discussed and significant applications and connections to certain practically interesting problems are mentioned.
A noisy stabilized Kuramoto–Sivashinsky equation is analyzed by stochastic decomposition. For val... more A noisy stabilized Kuramoto–Sivashinsky equation is analyzed by stochastic decomposition. For values of the control parameter for which periodic stationary patterns exist, the dynamics can be decomposed into diffusive and transverse parts which act on a stochastic potential. The relative positions of stationary states in the stochastic global potential landscape can be obtained from the topology spanned by the low-lying eigenmodes which interconnect them. Numerical simulations confirm the predicted landscape. The transverse component also predicts a universal class of vortex-like circulations around fixed points. These drive nonlinear drifting and limit cycle motion of the underlying periodic structure in certain regions of parameter space. Our findings might be relevant in studies of other nonlinear systems such as deep learning neural networks.
Schematic diagrams of metabolic network, heatmaps and box plots summary of the calculated fluxes ... more Schematic diagrams of metabolic network, heatmaps and box plots summary of the calculated fluxes are shown in the supporting figures.
Proceedings of the National Academy of Sciences, 2020
Significance Vortex or pattern formations are caused by nonlinear interactions within a complex s... more Significance Vortex or pattern formations are caused by nonlinear interactions within a complex system far from equilibrium. They cannot be well described by variational methods based on traditional potential functions. We aim to bridge the gap in this research. A previously developed stochastic decomposition on finite dimensions is extended to continuous nonlinear partial differential equations. Using a noisy stabilized Kuramoto–Sivashinsky equation as a role model, we show that a certain process of pattern selections can be viewed as stochastically driven on a global potential landscape, with a topology of an interconnected network of saddle points. The approach paves a way to further explore nonlinear phenomena under the general umbrella of statistical physics.
We show that in the recent artificial light-harvesting experiment [Angewandte Chemie Intl. Ed. 55... more We show that in the recent artificial light-harvesting experiment [Angewandte Chemie Intl. Ed. 55, 2759 (2016)] on organic nanocrystals self-assembled from difluoroboron chromophores, the spontaneous emission of an excited pigment should undergo a two-step process. It would first decay to an excitonic polariton confined by cavity resonance via strong photon-exciton coupling.
The production of secondary metabolites, while important for bioengineering purposes, presents a ... more The production of secondary metabolites, while important for bioengineering purposes, presents a paradox in itself. Though widely existing in plants and bacteria, they have no definite physiological roles. Yet in both native habitats and laboratories, their production appears robust and follows apparent metabolic switches. We show in this work that the enzyme-catalysed process may improve the metabolic stability of the cells. The latter can be responsible for the overall metabolic behaviours such as dynamic metabolic landscape, metabolic switches and robustness, which can in turn affect the genetic formation of the organism in question. Mangrove-derived Streptomyces xiamenensis 318, with a relatively compact genome for secondary metabolism, is used as a model organism in our investigation. Integrated studies via kinetic metabolic modelling, transcriptase measurements and metabolic profiling were performed on this strain. Our results demonstrate that the secondary metabolites increas...
Improvement in the survival rate of gastric cancer, a prevalent global malignancy and the leading... more Improvement in the survival rate of gastric cancer, a prevalent global malignancy and the leading cause of cancer-related mortality calls for more avenues in molecular therapy. This work aims to comprehend drug resistance and exploration of multiple-drug combinations for enhanced therapeutic treatment. An endogenous network modeling clinic data with core gastric cancer molecules, functional modules and pathways is constructed, which is then transformed into dynamics equations for in-silicon studies. Principal component analysis, hierarchical clustering, and K-means clustering are utilized to map the attractor domains of the stochastic model to the normal and pathological phenotypes identified from the clinical data. The analyses demonstrate gastric cancer as a cluster of stable states emerging within the stochastic dynamics and elucidate the cause of resistance to anti-VEGF monotherapy in cancer treatment as the limitation of single pathway in preventing the cancer progression. The feasibility of multiple objectives of therapy targeting specified molecules and/or pathways is explored. This study verifies the rationality of the platform of endogenous network modeling, which contributes to the development of cross-functional multitarget combinations in clinical trials.
Despite numerous recent studies on the Hall anomaly following the discovery of cuprate supercondu... more Despite numerous recent studies on the Hall anomaly following the discovery of cuprate superconductivity, the origin of this phenomenon remains contentious. We demonstrate that a previously proposed mechanism, in which vacancy-on-fragment of the flux-line crystal, provides an alternative explanation for the observations of Bi 2 Sr 2 CaCu 2 O x thin films made by Nitzav and Kanigel [Phys. Rev. B. 107, 094516 (2023)], without the need for adjustable parameters. Specifically, we show that the power-law behavior of ρ xy over ρ xx , with and without sign reversal, is consistent with the picture of vacancies versus fragments. Interestingly, we find that the effective length of vortex lines is consistently 1.5 unit cells (UC) across different experiments, independent of film thickness.
Bulletin of the American Physical Society, Mar 3, 2020
We uncover a novel phenomenon from a recent artificial light-harvesting experiment [P.-Z. Chen et... more We uncover a novel phenomenon from a recent artificial light-harvesting experiment [P.-Z. Chen et al., Angew. Chem., Int. Ed. Engl. 55, 2759 (2016)] on organic nanocrystals of self-assembled difluoroboron chromophores. A resonant confinement of a polariton under strong photon-exciton coupling is predicted to exist within the microcavity of the crystal's own natural boundaries. Moreover, the radiative energy of a localized exciton falls into the spectrum of confinement. Hence, in the experiment, the spontaneous emission of an excited pigment would undergo a two-step process. It should first decay to an excitonic polariton trapped by the cavity resonance. The intermediate polariton could then funnel the energy directly to a doped acceptor, leading to the over 90% transfer efficiency observed at less than 1=1000 acceptor=donor ratio. The proposed mechanism is supported by parameter-free analyses entirely based on experiment data. Our finding may imply possible polariton-mediated pathways for energy transfers in biological photosynthesis.
Stochastic gradient descent (SGD), a widely used algorithm in deep-learning neural networks has a... more Stochastic gradient descent (SGD), a widely used algorithm in deep-learning neural networks has attracted continuing studies for the theoretical principles behind its success. A recent work reports an anomaly (inverse) relation between the variance of neural weights and the landscape flatness of the loss function driven under SGD [Feng & Tu, PNAS 118, 0027 (2021)]. To investigate this seemingly violation of statistical physics principle, the properties of SGD near fixed points are analysed via a dynamic decomposition method. Our approach recovers the true "energy" function under which the universal Boltzmann distribution holds. It differs from the cost function in general and resolves the paradox raised by the the anomaly. The study bridges the gap between the classical statistical mechanics and the emerging discipline of artificial intelligence, with potential for better algorithms to the latter.
Quantum computing is a new way to processing quantum information by using superposition and entan... more Quantum computing is a new way to processing quantum information by using superposition and entanglement of the quantum system. Quantum state's vast Hilbert space allows it to perform operations that classical computers cannot compared with classical computing, quantum computing has unique advantages in dealing with some complex problems, so it has attracted wide attention. Computing a single qubit is the first of seven fundamental stages needed to achieve a large-scale quantum computer that is universal, scalable and fault-tolerant. In other words, the primary task of quantum computing is the careful preparation and precise regulation of qubits. At present, the physical systems that can be used as qubits include superconducting qubits, semiconductor qubits, ion trap systems and nitrogen-vacancy (NV) color centers, etc. These physical systems have made great progress in terms of decoherence time and scalability. Due to the vulnerability of qubits, ambient thermal noise can cause...
Stochastic gradient descent (SGD), a widely used algorithm in deep-learning neural networks has a... more Stochastic gradient descent (SGD), a widely used algorithm in deep-learning neural networks has attracted continuing studies for the theoretical principles behind its success. A recent work reports an anomaly (inverse) relation between the variance of neural weights and the landscape flatness of the loss function driven under SGD [Feng & Tu, PNAS 118, 0027 (2021)]. To investigate this seemingly violation of statistical physics principle, the properties of SGD near fixed points are analysed via a dynamic decomposition method. Our approach recovers the true "energy" function under which the universal Boltzmann distribution holds. It differs from the cost function in general and resolves the paradox raised by the the anomaly. The study bridges the gap between the classical statistical mechanics and the emerging discipline of artificial intelligence, with potential for better algorithms to the latter.
Hall anomaly, as appears in the mixed-state Hall resistivity of type-II superconductors, has had ... more Hall anomaly, as appears in the mixed-state Hall resistivity of type-II superconductors, has had numerous theories but yet a consensus on its origin. In this work, we conducted a quantitative analysis of the magnetotransport measurements on BSCCO thin films by Zhao et al. [Phys. Rev. Lett. 122, 247001 (2019)] and validate a previously proposed vacancy mechanism [cf. J. Phys. Condens. Matter. 10, L677 (1998)] with many-body vortex correlations for the phenomenon. The model attributes the Hall anomaly to the motion of vacancies in pinned fragments of vortex lattice. Its validity is first examined by an exploration on the vortex states near the Kosterlitz-Thouless transition on the vortex crystal. Comparisons are then carried out between the measured activation energies with the calculated creation energy of the vortex-anti-vortex pair and the vacancy energy on the flux-line lattice, with no adjustable parameter. Our analysis elucidates the theoretical basis and prerequisites of the vacancy model. In particular, the vacancy activation energies are an order of magnitude smaller than that of a sole vortex line. The proposed mechanism may provide a macro-theoretical framework for other studies.
The production of secondary metabolites, while important for bioengineering purposes, presents a ... more The production of secondary metabolites, while important for bioengineering purposes, presents a paradox in itself. Though widely existing in plants and bacteria, they have no definite physiological roles. Yet in both native habitats and laboratories, their production appears robust and follows apparent metabolic switches. We show in this work that the enzyme-catalysed process may improve the metabolic stability of the cells. The latter can be responsible for the overall metabolic behaviours such as dynamic metabolic landscape, metabolic switches and robustness, which can in turn affect the genetic formation of the organism in question. Mangrove-derived <i>Streptomyces xiamenensis</i> 318, with a relatively compact genome for secondary metabolism, is used as a model organism in our investigation. Integrated studies via kinetic metabolic modelling, transcriptase measurements and metabolic profiling were performed on this strain. Our results demonstrate that the secondary ...
Quantum dynamics of a particle coupled to a fermionic environment is considered, with particular ... more Quantum dynamics of a particle coupled to a fermionic environment is considered, with particular emphasis on the formulation of macroscopic quantum phenomena. The framework is based on a path integral formalism for the realtime density matrix. After integrating out of the fermion variables of the environment, we embed the whole environmental effects on the particle into the so-called influence functional in analogy to Feynman and Vernon's initial work. We then show that to the second order of the coupling constant, the exponent of the influence functional is in exact agreement with that due to a linear dissipative environment (boson bath). Having obtained this, we turn to a specific model in which the influence functional can be exactly evaluated in a long-time limit (long compared to the inverse of the cutoff frequency of the environmental spectrum). In this circumstance, we mainly address our attention to the quantum mechanical representation of the system-plus-environment from the known classical properties of the particle. It is shown that, in particular, the equivalence between the fermion bath and the boson bath is generally correct for a singlechannel coupling provided we make a simple mapping between the nonlinear interaction functions of the baths. Finally, generalizations of the model to more complicated situations are discussed and significant applications and connections to certain practically interesting problems are mentioned.
A noisy stabilized Kuramoto–Sivashinsky equation is analyzed by stochastic decomposition. For val... more A noisy stabilized Kuramoto–Sivashinsky equation is analyzed by stochastic decomposition. For values of the control parameter for which periodic stationary patterns exist, the dynamics can be decomposed into diffusive and transverse parts which act on a stochastic potential. The relative positions of stationary states in the stochastic global potential landscape can be obtained from the topology spanned by the low-lying eigenmodes which interconnect them. Numerical simulations confirm the predicted landscape. The transverse component also predicts a universal class of vortex-like circulations around fixed points. These drive nonlinear drifting and limit cycle motion of the underlying periodic structure in certain regions of parameter space. Our findings might be relevant in studies of other nonlinear systems such as deep learning neural networks.
Schematic diagrams of metabolic network, heatmaps and box plots summary of the calculated fluxes ... more Schematic diagrams of metabolic network, heatmaps and box plots summary of the calculated fluxes are shown in the supporting figures.
Proceedings of the National Academy of Sciences, 2020
Significance Vortex or pattern formations are caused by nonlinear interactions within a complex s... more Significance Vortex or pattern formations are caused by nonlinear interactions within a complex system far from equilibrium. They cannot be well described by variational methods based on traditional potential functions. We aim to bridge the gap in this research. A previously developed stochastic decomposition on finite dimensions is extended to continuous nonlinear partial differential equations. Using a noisy stabilized Kuramoto–Sivashinsky equation as a role model, we show that a certain process of pattern selections can be viewed as stochastically driven on a global potential landscape, with a topology of an interconnected network of saddle points. The approach paves a way to further explore nonlinear phenomena under the general umbrella of statistical physics.
We show that in the recent artificial light-harvesting experiment [Angewandte Chemie Intl. Ed. 55... more We show that in the recent artificial light-harvesting experiment [Angewandte Chemie Intl. Ed. 55, 2759 (2016)] on organic nanocrystals self-assembled from difluoroboron chromophores, the spontaneous emission of an excited pigment should undergo a two-step process. It would first decay to an excitonic polariton confined by cavity resonance via strong photon-exciton coupling.
The production of secondary metabolites, while important for bioengineering purposes, presents a ... more The production of secondary metabolites, while important for bioengineering purposes, presents a paradox in itself. Though widely existing in plants and bacteria, they have no definite physiological roles. Yet in both native habitats and laboratories, their production appears robust and follows apparent metabolic switches. We show in this work that the enzyme-catalysed process may improve the metabolic stability of the cells. The latter can be responsible for the overall metabolic behaviours such as dynamic metabolic landscape, metabolic switches and robustness, which can in turn affect the genetic formation of the organism in question. Mangrove-derived Streptomyces xiamenensis 318, with a relatively compact genome for secondary metabolism, is used as a model organism in our investigation. Integrated studies via kinetic metabolic modelling, transcriptase measurements and metabolic profiling were performed on this strain. Our results demonstrate that the secondary metabolites increas...
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Papers by Yong-Cong Chen