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We consider a version of large population games whose players compete for resources using strategies with adaptable preferences. The system efficiency is measured by the variance of the decisions. In the regime where the system can be plagued by the maladaptive behavior of the players, we find that diversity among the players improves the system efficiency, though it slows the convergence to the steady state. Diversity causes a mild spread of resources at the transient state, but reduces the uneven distribution of resources in the steady state.

The chaotic complexity properties of semiconductor lasers in the chaotic synchronization systems are investigated numerically, based on the information theory based quantifier, the permutation entropy (PE). We find that, on the one hand, the degree of complexity for the master laser increases with the feedback strength firstly and then saturate at higher feedback strength, but are hardly affected by the feedback delay. On the other hand, for the slave laser, the complexity degree is closer to that for the master laser when the high quality chaos synchronization is obtained, which shows that, the PE method is a successful quantifier to evaluate the degree of complexity for the chaotic signals in chaos synchronization systems, and can be considered as a complementary tool to observe the synchronization quality.

We discuss the performance of the Search and Fourier Transform algorithms on a hybrid computer constituted of classical and quantum processors working together. We show that this semi-quantum computer would be an improvement over a pure classical architecture, no matter how few qubits are available and, therefore, it suggests an easier implementable technology than a pure quantum computer with arbitrary number of qubits.

The production of "work" in a number of chemical processes (of particular applicability to biology) is analyzed, and studied as a function of a system's internal and external parameters.

We discuss models of computing that are beyond classical. The primary motivation is to unearth the cause of non-classical advantages in computation. Completeness results from computational complexity theory lead to the identification of very disparate problems, and offer a kaleidoscopic view into the realm of quantum enhancements in computation. Emphasis is placed on the "power of one qubit" model, and the boundary between quantum and classical correlations as delineated by quantum discord. A recent result by Eastin on the role of this boundary in the efficient classical simulation of quantum computation is discussed. Perceived drawbacks in the interpretation of quantum discord as a relevant certificate of quantum enhancements are addressed.

In the past decades, all of the efforts at quantifying systems complexity with a general tool has usually relied on using Shannon's classical information framework to address the disorder of the system through the Boltzmann–Gibbs–Shannon entropy, or one of its extensions. However, in recent years, there were some attempts to tackle the quantification of algorithmic complexities in quantum systems based on the Kolmogorov algorithmic complexity, obtaining some discrepant results against the classical approach. Therefore, an approach to the complexity measure is proposed here, using the quantum information formalism, taking advantage of the generality of the classical-based complexities, and being capable of expressing these systems' complexity on other framework than its algorithmic counterparts. To do so, the Shiner–Davison–Landsberg (SDL) complexity framework is considered jointly with linear entropy for the density operators representing the analyzed systems formalism along with the tangle for the entanglement measure. The proposed measure is then applied in a family of maximally entangled mixed state.

We investigate the possibility to obtain higly multipartite-entangled states as non-degenerate eigenstates of Hamiltonians that involve only short-range and few-body interactions. We study small-size systems (with a number of qubits ranging from three to five) and search for Hamiltonians with a maximally multipartite entangled state (MMES) as a non-degenerate eigenstate. We then find conditions, including bounds on the number of coupled qubits, to build a Hamiltonian with a Greenberger–Horne–Zeilinger (GHZ) state as a non-degenerate eigenstate. We finally comment on possible applications.

Heterogeneity is a hallmark of all cancers. Tumor heterogeneity is found at different levels — interpatient, intrapatient, and intratumor heterogeneity. All of them pose challenges for clinical treatments. The latter two scenarios can also increase the risk of developing drug resistance. Although the existence of tumor heterogeneity has been known for two centuries, a clear understanding of its origin is still elusive, especially at the level of intratumor heterogeneity (ITH). The coexistence of different subpopulations within a single tumor has been shown to play crucial roles during all stages of carcinogenesis. Here, using concepts from evolutionary game theory and public goods game, often invoked in the context of the tragedy of commons, we explore how the interactions among subclone populations influence the establishment of ITH. By using an evolutionary model, which unifies several experimental results in distinct cancer types, we develop quantitative theoretical models for explaining data from in vitro experiments involving pancreatic cancer as well as in vivo data in glioblastoma multiforme. Such physical and mathematical models complement experimental studies, and could optimistically provide new ideas for the design of efficacious therapies for cancer patients.

Physics is a seamless dialogue with Nature that transcends the divisions made by practising physicists—often for convenience, often imposed by their own limitations. It is difficult to sustain the notion that one branch of physics can satisfactorily answer all the questions of Nature. I expand on this theme briefly, and also technically, using the example of hydrodynamic turbulence.

All complex life on Earth is composed of ‘eukaryotic’ cells. Eukaryotes arose just once in 4 billion years, via an endosymbiosis — bacteria entered a simple host cell, evolving into mitochondria, the ‘powerhouses’ of complex cells. Mitochondria lost most of their genes, retaining only those needed for respiration, giving eukaryotes ‘multi-bacterial’ power without the costs of maintaining thousands of complete bacterial genomes. These energy savings supported a substantial expansion in nuclear genome size, and far more protein synthesis from each gene.