1,042 research outputs found

    How much measurement independence is needed in order to demonstrate nonlocality?

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    If nonlocality is to be inferred from a violation of Bell's inequality, an important assumption is that the measurement settings are freely chosen by the observers, or alternatively, that they are random and uncorrelated with the hypothetical local variables. We study the case where this assumption is weakened, so that measurement settings and local variables are at least partially correlated. As we show, there is a connection between this type of model and models which reproduce nonlocal correlations by allowing classical communication between the distant parties, and a connection with models that exploit the detection loophole. We show that even if Bob's choices are completely independent, all correlations obtained from projective measurements on a singlet can be reproduced, with the correlation (measured by mutual information) between Alice's choice and local variables less than or equal to a single bit.Comment: 5 pages, 1 figure. v2 Various improvements in presentation. Results unchange

    Stochastic Simulation of Process Calculi for Biology

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    Biological systems typically involve large numbers of components with complex, highly parallel interactions and intrinsic stochasticity. To model this complexity, numerous programming languages based on process calculi have been developed, many of which are expressive enough to generate unbounded numbers of molecular species and reactions. As a result of this expressiveness, such calculi cannot rely on standard reaction-based simulation methods, which require fixed numbers of species and reactions. Rather than implementing custom stochastic simulation algorithms for each process calculus, we propose to use a generic abstract machine that can be instantiated to a range of process calculi and a range of reaction-based simulation algorithms. The abstract machine functions as a just-in-time compiler, which dynamically updates the set of possible reactions and chooses the next reaction in an iterative cycle. In this short paper we give a brief summary of the generic abstract machine, and show how it can be instantiated with the stochastic simulation algorithm known as Gillespie's Direct Method. We also discuss the wider implications of such an abstract machine, and outline how it can be used to simulate multiple calculi simultaneously within a common framework.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

    Integrated regulatory models for inference of subtype-specific susceptibilities in glioblastoma

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    Abstract Glioblastoma multiforme (GBM) is a highly malignant form of cancer that lacks effective treatment options or well‐defined strategies for personalized cancer therapy. The disease has been stratified into distinct molecular subtypes; however, the underlying regulatory circuitry that gives rise to such heterogeneity and its implications for therapy remain unclear. We developed a modular computational pipeline, Integrative Modeling of Transcription Regulatory Interactions for Systematic Inference of Susceptibility in Cancer (inTRINSiC), to dissect subtype‐specific regulatory programs and predict genetic dependencies in individual patient tumors. Using a multilayer network consisting of 518 transcription factors (TFs), 10,733 target genes, and a signaling layer of 3,132 proteins, we were able to accurately identify differential regulatory activity of TFs that shape subtype‐specific expression landscapes. Our models also allowed inference of mechanisms for altered TF behavior in different GBM subtypes. Most importantly, we were able to use the multilayer models to perform an in silico perturbation analysis to infer differential genetic vulnerabilities across GBM subtypes and pinpoint the MYB family member MYBL2 as a drug target specific for the Proneural subtype

    Classical simulation of entanglement swapping with bounded communication

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    Entanglement appears under two different forms in quantum theory, namely as a property of states of joint systems and as a property of measurement eigenstates in joint measurements. By combining these two aspects of entanglement, it is possible to generate nonlocality between particles that never interacted, using the protocol of entanglement swapping. We show that even in the more constraining bilocal scenario where distant sources of particles are assumed to be independent, i.e. to share no prior randomness, this process can be simulated classically with bounded communication, using only 9 bits in total. Our result thus provides an upper bound on the nonlocality of the process of entanglement swapping.Comment: 6 pages, 1 figur

    Herpesviruses shape tumour microenvironment through exosomal transfer of viral microRNAs

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    Metabolic changes within the cell and its niche affect cell fate and are involved in many diseases and disorders including cancer and viral infections. Kaposi's sarcoma-associated herpesvirus (KSHV) is the etiological agent of Kaposi's sarcoma (KS). KSHV latently infected cells express only a subset of viral genes, mainly located within the latency-associated region, among them 12 microRNAs. Notably, these miRNAs are responsible for inducing the Warburg effect in infected cells. Here we identify a novel mechanism enabling KSHV to manipulate the metabolic nature of the tumour microenvironment. We demonstrate that KSHV infected cells specifically transfer the virus-encoded microRNAs to surrounding cells via exosomes. This flow of genetic information results in a metabolic shift toward aerobic glycolysis in the surrounding non-infected cells. Importantly, this exosome-mediated metabolic reprogramming of neighbouring cells supports the growth of infected cells, thereby contributing to viral fitness. Finally, our data show that this miRNA transfer-based regulation of cell metabolism is a general mechanism used by other herpesviruses, such as EBV, as well as for the transfer of non-viral onco-miRs. This exosome-based crosstalk provides viruses with a mechanism for non-infectious transfer of genetic material without production of new viral particles, which might expose them to the immune system. We suggest that viruses and cancer cells use this mechanism to shape a specific metabolic niche that will contribute to their fitness

    The nuclear reaction waiting points, Mg22, Si26, S30, and Ar34, and bolometrically double peaked type I X-ray bursts

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    Type I X-ray bursts with a double peak in the bolometric luminosity have been observed from several sources. The separation between the two peaks are on the order of a few seconds. We propose a nuclear waiting point impedance in the thermonuclear reaction flow to explain these observations. Nuclear structure information suggests the potential waiting points: Mg22, Si26, S30 and Ar34, which arise in conditions, where a further reaction flow has to await a beta-decay, because the (alpha,p)-reaction is too weak to overcome the target Coulomb-barrier and the (p,gamma)-reaction is quenched by photo-disintegration at the burst temperature. The conclusion is that the effects of the experimentally unknown S30(alpha,p)Cl33 and Ar34(alpha,p)K37 might be directly visible in the observation of X-ray burst light curves.Comment: 5 pages, 3 figures, submitted to Astrophys. J. Let

    Narrative-based computational modelling of the Gp130/JAK/STAT signalling pathway.

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    BACKGROUND: Appropriately formulated quantitative computational models can support researchers in understanding the dynamic behaviour of biological pathways and support hypothesis formulation and selection by "in silico" experimentation. An obstacle to widespread adoption of this approach is the requirement to formulate a biological pathway as machine executable computer code. We have recently proposed a novel, biologically intuitive, narrative-style modelling language for biologists to formulate the pathway which is then automatically translated into an executable format and is, thus, usable for analysis via existing simulation techniques. RESULTS: Here we use a high-level narrative language in designing a computational model of the gp130/JAK/STAT signalling pathway and show that the model reproduces the dynamic behaviour of the pathway derived by biological observation. We then "experiment" on the model by simulation and sensitivity analysis to define those parameters which dominate the dynamic behaviour of the pathway. The model predicts that nuclear compartmentalisation and phosphorylation status of STAT are key determinants of the pathway and that alternative mechanisms of signal attenuation exert their influence on different timescales. CONCLUSION: The described narrative model of the gp130/JAK/STAT pathway represents an interesting case study showing how, by using this approach, researchers can model biological systems without explicitly dealing with formal notations and mathematical expressions (typically used for biochemical modelling), nevertheless being able to obtain simulation and analysis results. We present the model and the sensitivity analysis results we have obtained, that allow us to identify the parameters which are most sensitive to perturbations. The results, which are shown to be in agreement with existing mathematical models of the gp130/JAK/STAT pathway, serve us as a form of validation of the model and of the approach itself

    Computational Indistinguishability between Quantum States and Its Cryptographic Application

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    We introduce a computational problem of distinguishing between two specific quantum states as a new cryptographic problem to design a quantum cryptographic scheme that is "secure" against any polynomial-time quantum adversary. Our problem, QSCDff, is to distinguish between two types of random coset states with a hidden permutation over the symmetric group of finite degree. This naturally generalizes the commonly-used distinction problem between two probability distributions in computational cryptography. As our major contribution, we show that QSCDff has three properties of cryptographic interest: (i) QSCDff has a trapdoor; (ii) the average-case hardness of QSCDff coincides with its worst-case hardness; and (iii) QSCDff is computationally at least as hard as the graph automorphism problem in the worst case. These cryptographic properties enable us to construct a quantum public-key cryptosystem, which is likely to withstand any chosen plaintext attack of a polynomial-time quantum adversary. We further discuss a generalization of QSCDff, called QSCDcyc, and introduce a multi-bit encryption scheme that relies on similar cryptographic properties of QSCDcyc.Comment: 24 pages, 2 figures. We improved presentation, and added more detail proofs and follow-up of recent wor

    The Hilbertian Tensor Norm and Entangled Two-Prover Games

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    We study tensor norms over Banach spaces and their relations to quantum information theory, in particular their connection with two-prover games. We consider a version of the Hilbertian tensor norm γ2\gamma_2 and its dual γ2∗\gamma_2^* that allow us to consider games with arbitrary output alphabet sizes. We establish direct-product theorems and prove a generalized Grothendieck inequality for these tensor norms. Furthermore, we investigate the connection between the Hilbertian tensor norm and the set of quantum probability distributions, and show two applications to quantum information theory: firstly, we give an alternative proof of the perfect parallel repetition theorem for entangled XOR games; and secondly, we prove a new upper bound on the ratio between the entangled and the classical value of two-prover games.Comment: 33 pages, some of the results have been obtained independently in arXiv:1007.3043v2, v2: an error in Theorem 4 has been corrected; Section 6 rewritten, v3: completely rewritten in order to improve readability; title changed; references added; published versio
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