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Готові списки джерел за темами / Causal set / Статті в журналах

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Статті в журналах з теми "Causal set"

Автор: Grafiati

Опубліковано: 14 березня 2023

Оновлено: 31 липня 2025

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1

Surya, Sumati. "Causal set topology." Theoretical Computer Science 405, no. 1-2 (2008): 188–97. http://dx.doi.org/10.1016/j.tcs.2008.06.033.

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2

He, Song, and David Rideout. "A causal set black hole." Classical and Quantum Gravity 26, no. 12 (2009): 125015. http://dx.doi.org/10.1088/0264-9381/26/12/125015.

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3

Sverdlov, Roman. "Bosonic Fields in Causal Set Theory." International Journal of Theoretical Physics 60, no. 4 (2021): 1481–506. http://dx.doi.org/10.1007/s10773-021-04772-6.

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4

Sorkin, Rafael D., and Yasaman K. Yazdi. "Entanglement entropy in causal set theory." Classical and Quantum Gravity 35, no. 7 (2018): 074004. http://dx.doi.org/10.1088/1361-6382/aab06f.

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5

Bombelli, Luca, Joohan Lee, David Meyer, and Rafael D. Sorkin. "Space-time as a causal set." Physical Review Letters 59, no. 5 (1987): 521–24. http://dx.doi.org/10.1103/physrevlett.59.521.

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6

Glaser, Lisa. "Causal set actions in various dimensions." Journal of Physics: Conference Series 306 (July 8, 2011): 012041. http://dx.doi.org/10.1088/1742-6596/306/1/012041.

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7

Major, Seth A., David Rideout, and Sumati Surya. "Spatial hypersurfaces in causal set cosmology." Classical and Quantum Gravity 23, no. 14 (2006): 4743–51. http://dx.doi.org/10.1088/0264-9381/23/14/011.

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8

Philpott, L. "Particle simulations in causal set theory." Classical and Quantum Gravity 27, no. 4 (2010): 042001. http://dx.doi.org/10.1088/0264-9381/27/4/042001.

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9

Criscuolo, A., and H. Waelbroeck. "Causal set dynamics: a toy model." Classical and Quantum Gravity 16, no. 6 (1999): 1817–32. http://dx.doi.org/10.1088/0264-9381/16/6/315.

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10

Wüthrich, Christian, and Craig Callender. "What Becomes of a Causal Set?" British Journal for the Philosophy of Science 68, no. 3 (2017): 907–25. http://dx.doi.org/10.1093/bjps/axv040.

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11

Drici, Z., F. A. Mcrae, and J. Vasundhara Devi. "Set differential equations with causal operators." Mathematical Problems in Engineering 2005, no. 2 (2005): 185–94. http://dx.doi.org/10.1155/mpe.2005.185.

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12

Dowker, Fay, and Lisa Glaser. "Causal set d'Alembertians for various dimensions." Classical and Quantum Gravity 30, no. 19 (2013): 195016. http://dx.doi.org/10.1088/0264-9381/30/19/195016.

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13

Saravani, Mehdi, and Siavash Aslanbeigi. "On the causal set–continuum correspondence." Classical and Quantum Gravity 31, no. 20 (2014): 205013. http://dx.doi.org/10.1088/0264-9381/31/20/205013.

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14

Carlip, S. "Dimensional reduction in causal set gravity." Classical and Quantum Gravity 32, no. 23 (2015): 232001. http://dx.doi.org/10.1088/0264-9381/32/23/232001.

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15

Cunningham, William J., and Dmitri Krioukov. "Causal set generator and action computer." Computer Physics Communications 233 (December 2018): 123–33. http://dx.doi.org/10.1016/j.cpc.2018.06.008.

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16

Philpott, Lydia, Fay Dowker, and Rafael Sorkin. "Massless particle diffusion in causal set theory." Journal of Physics: Conference Series 174 (June 1, 2009): 012048. http://dx.doi.org/10.1088/1742-6596/174/1/012048.

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17

Sverdlov, Roman, and Luca Bombelli. "Gravity and matter in causal set theory." Classical and Quantum Gravity 26, no. 7 (2009): 075011. http://dx.doi.org/10.1088/0264-9381/26/7/075011.

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18

Dowker, Fay, and Stav Zalel. "Evolution of universes in causal set cosmology." Comptes Rendus Physique 18, no. 3-4 (2017): 246–53. http://dx.doi.org/10.1016/j.crhy.2017.03.002.

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19

Eichhorn, Astrid, and Sebastian Mizera. "Spectral dimension in causal set quantum gravity." Classical and Quantum Gravity 31, no. 12 (2014): 125007. http://dx.doi.org/10.1088/0264-9381/31/12/125007.

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20

Yu, Kui, Lin Liu, and Jiuyong Li. "A Unified View of Causal and Non-causal Feature Selection." ACM Transactions on Knowledge Discovery from Data 15, no. 4 (2021): 1–46. http://dx.doi.org/10.1145/3436891.

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Анотація:

In this article, we aim to develop a unified view of causal and non-causal feature selection methods. The unified view will fill in the gap in the research of the relation between the two types of methods. Based on the Bayesian network framework and information theory, we first show that causal and non-causal feature selection methods share the same objective. That is to find the Markov blanket of a class attribute, the theoretically optimal feature set for classification. We then examine the assumptions made by causal and non-causal feature selection methods when searching for the optimal fea

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21

BRIGHTWELL, GRAHAM, and MALWINA LUCZAK. "Order-Invariant Measures on Fixed Causal Sets." Combinatorics, Probability and Computing 21, no. 3 (2012): 330–57. http://dx.doi.org/10.1017/s0963548311000721.

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A causal set is a countably infinite poset in which every element is above finitely many others; causal sets are exactly the posets that have a linear extension with the order-type of the natural numbers; we call such a linear extension a natural extension. We study probability measures on the set of natural extensions of a causal set, especially those measures having the property of order-invariance: if we condition on the set of the bottom k elements of the natural extension, each feasible ordering among these k elements is equally likely. We give sufficient conditions for the existence and

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22

Surya, Sumati, Nomaan X, and Yasaman K. Yazdi. "Entanglement entropy of causal set de Sitter horizons." Classical and Quantum Gravity 38, no. 11 (2021): 115001. http://dx.doi.org/10.1088/1361-6382/abf279.

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23

Machet, Ludovico, and Jinzhao Wang. "On the horizon entropy of a causal set." Classical and Quantum Gravity 38, no. 8 (2021): 085004. http://dx.doi.org/10.1088/1361-6382/abe957.

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24

Asato, Yu. "Black holes and singularities in causal set gravity." Classical and Quantum Gravity 36, no. 19 (2019): 195008. http://dx.doi.org/10.1088/1361-6382/ab3c18.

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25

Dowker, Fay, Nazireen Imambaccus, Amelia Owens, Rafael Sorkin, and Stav Zalel. "A manifestly covariant framework for causal set dynamics." Classical and Quantum Gravity 37, no. 8 (2020): 085003. http://dx.doi.org/10.1088/1361-6382/ab719c.

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26

Major, Seth, David Rideout, and Sumati Surya. "On recovering continuum topology from a causal set." Journal of Mathematical Physics 48, no. 3 (2007): 032501. http://dx.doi.org/10.1063/1.2435599.

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27

Moore, Cristopher. "Comment on ‘‘Space-time as a causal set’’." Physical Review Letters 60, no. 7 (1988): 655. http://dx.doi.org/10.1103/physrevlett.60.655.

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28

Leva, Alberto, and Luca Bascetta. "Set point tracking optimisation by causal nonparametric modelling." Automatica 43, no. 11 (2007): 1984–91. http://dx.doi.org/10.1016/j.automatica.2007.04.002.

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29

Duffy, Callum F., Joshua Y. L. Jones, and Yasaman K. Yazdi. "Entanglement entropy of disjoint spacetime intervals in causal set theory." Classical and Quantum Gravity 39, no. 7 (2022): 075017. http://dx.doi.org/10.1088/1361-6382/ac5493.

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Анотація:

Abstract A more complete understanding of entanglement entropy in a covariant manner could inform the search for quantum gravity. We build on work in this direction by extending previous results to disjoint regions in 1 + 1D. We investigate the entanglement entropy of a scalar field in disjoint intervals within the causal set framework, using the spacetime commutator and correlator, i Δ and W (or the Pauli–Jordan and Wightman functions). A new truncation scheme for disjoint causal diamonds is presented, which follows from the single diamond truncation scheme. We investigate setups including tw

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30

Fomin, V. N. "Minimization of a functional over the set of causal operators of causal Hilbert space." Journal of Mathematical Sciences 77, no. 4 (1995): 3362–90. http://dx.doi.org/10.1007/bf02364867.

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31

Misangyi, Vilmos F., Thomas Greckhamer, Santi Furnari, Peer C. Fiss, Donal Crilly, and Ruth Aguilera. "Embracing Causal Complexity." Journal of Management 43, no. 1 (2016): 255–82. http://dx.doi.org/10.1177/0149206316679252.

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Causal complexity has long been recognized as a ubiquitous feature underlying organizational phenomena, yet current theories and methodologies in management are for the most part not well-suited to its direct study. The introduction of the Qualitative Comparative Analysis (QCA) configurational approach has led to a reinvigoration of configurational theory that embraces causal complexity explicitly. We argue that the burgeoning research using QCA represents more than a novel methodology; it constitutes the emergence of a neo-configurational perspective to the study of management and organizatio

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32

Long, Susan B., and Richard H. Evans. "Matching Attribute set and Attitude Model." Psychological Reports 60, no. 3_part_2 (1987): 1087–96. http://dx.doi.org/10.1177/0033294187060003-214.1.

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The attribute set/attitude model relationship recently proposed by Myers and Shocker was examined using correlational and (LISREL) causal analysis. Compared against more traditional single-attitude model approaches (Ahtola, Adequacy-Importance, and Fishbein), Myers and Shocker's mixed model appears promising. It matched the attitude model which best predicted behavioral intentions for two out of three product attribute sets, and along with the Fishbein model, produced a satisfactory fit with the hypothesized causal structure. However, when the alternative attitude models were compared using a

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33

Triantafillou, Sofia, and Greg Cooper. "Learning Adjustment Sets from Observational and Limited Experimental Data." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 11 (2021): 9940–48. http://dx.doi.org/10.1609/aaai.v35i11.17194.

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Estimating causal effects from observational data is not always possible due to confounding. Identifying a set of appropriate covariates (adjustment set) and adjusting for their influence can remove confounding bias; however, such a set is often not identifiable from observational data alone. Experimental data allow unbiased causal effect estimation, but are typically limited in sample size and can therefore yield estimates of high variance. Moreover, experiments are often performed on a different (specialized) population than the population of interest. In this work, we introduce a method tha

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34

Du, Yunzhou, and Qiuchen Liu. "Testing Explicit Mediation Models by Set-Theoretic Causal Complexity." Academy of Management Proceedings 2021, no. 1 (2021): 14898. http://dx.doi.org/10.5465/ambpp.2021.14898abstract.

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35

Krugly, Alexey L., and Ivan A. Tserkovnikov. "An example of numerical simulation in causal set dynamics." Journal of Physics: Conference Series 442 (June 10, 2013): 012042. http://dx.doi.org/10.1088/1742-6596/442/1/012042.

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36

Eichhorn, Astrid, Sebastian Mizera, and Sumati Surya. "Echoes of asymptotic silence in causal set quantum gravity." Classical and Quantum Gravity 34, no. 16 (2017): 16LT01. http://dx.doi.org/10.1088/1361-6382/aa7d1b.

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37

Glaser, Lisa, Denjoe O’Connor, and Sumati Surya. "Finite size scaling in 2d causal set quantum gravity." Classical and Quantum Gravity 35, no. 4 (2018): 045006. http://dx.doi.org/10.1088/1361-6382/aa9540.

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38

Dowker, Fay, and Sumati Surya. "Observables in extended percolation models of causal set cosmology." Classical and Quantum Gravity 23, no. 4 (2006): 1381–90. http://dx.doi.org/10.1088/0264-9381/23/4/018.

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39

Glaser, Lisa. "A closed form expression for the causal set d’Alembertian." Classical and Quantum Gravity 31, no. 9 (2014): 095007. http://dx.doi.org/10.1088/0264-9381/31/9/095007.

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40

Neal, Zachary. "Creative Employment and Jet Set Cities: Disentangling Causal Effects." Urban Studies 49, no. 12 (2012): 2693–709. http://dx.doi.org/10.1177/0042098011431282.

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41

Wang, Zhuoyao, Rui-Wei Zhao, Rui Feng, and Cheng Jin. "Toward Causal and Evidential Open-Set Temporal Action Detection." IEEE Access 13 (2025): 51440–57. https://doi.org/10.1109/access.2025.3553717.

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42

ORTIGUEIRA, MANUEL D., MARGARITA RIVERO, and JUAN J. TRUJILLO. "THE INCREMENTAL RATIO BASED CAUSAL FRACTIONAL CALCULUS." International Journal of Bifurcation and Chaos 22, no. 04 (2012): 1250078. http://dx.doi.org/10.1142/s0218127412500782.

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Анотація:

The generalized incremental ratio fractional derivative is revised and its main properties deduced. It is shown that in the case of analytic functions, it enjoys some interesting properties like: linearity and causality and has a semi-group structure. Some simple examples are presented. The enlargement of the set of functions for which the group properties of the fractional derivative are valid is done. With this, it is shown that some well-known results are valid in a more general set-up. Some examples are presented.

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43

Pechsiri, Chaveevan, and Rapepun Piriyakul. "Causal Pathway Extraction from Web-Board Documents." Applied Sciences 11, no. 21 (2021): 10342. http://dx.doi.org/10.3390/app112110342.

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Анотація:

This research aim is to extract causal pathways, particularly disease causal pathways, through cause-effect relation (CErel) extraction from web-board documents. The causal pathways benefit people with a comprehensible representation approach to disease complication. A causative/effect-concept expression is based on a verb phrase of an elementary discourse unit (EDU) or a simple sentence. The research has three main problems; how to determine CErel on an EDU-concept pair containing both causative and effect concepts in one EDU, how to extract causal pathways from EDU-concept pairs having CErel

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44

Nanmo, Hisayoshi, and Manabu Kuroki. "PCM Selector: Penalized Covariate-Mediator Selection Operator for Evaluating Linear Causal Effects." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 25 (2025): 26851–58. https://doi.org/10.1609/aaai.v39i25.34889.

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Анотація:

For a data-generating process for random variables that can be described with a linear structural equation model, we consider a situation in which (i) a set of covariates satisfying the back-door criterion cannot be observed or (ii) such a set can be observed, but standard statistical estimation methods cannot be applied to estimate causal effects because of multicollinearity/high-dimensional data problems. We propose a novel two-stage penalized regression approach, the penalized covariate-mediator selection operator (PCM Selector), to estimate the causal effects in such scenarios. Unlike exis

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45

Reid, D. D. "Discrete quantum gravity and causal sets." Canadian Journal of Physics 79, no. 1 (2001): 1–16. http://dx.doi.org/10.1139/p01-032.

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Анотація:

This paper provides a thorough introduction to the physical and conceptual need for a theory of quantum gravity; some knowledge of general relativity and nonrelativistic quantum mechanics is assumed. A theory of quantum gravity would have wide-ranging implications for high-energy physics, astrophysics, and cosmology. The paper goes on to describe an important approach to quantum gravity that is not well known outside of the quantum gravity research community causal sets. The causal-set approach falls within the framework of discrete quantum gravity, which considers the possibility that the s

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46

Rohlfing, Ingo, and Carsten Q. Schneider. "A Unifying Framework for Causal Analysis in Set-Theoretic Multimethod Research." Sociological Methods & Research 47, no. 1 (2016): 37–63. http://dx.doi.org/10.1177/0049124115626170.

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Анотація:

The combination of Qualitative Comparative Analysis (QCA) with process tracing, which we call set-theoretic multimethod research (MMR), is steadily becoming more popular in empirical research. Despite the fact that both methods have an elected affinity based on set theory, it is not obvious how a within-case method operating in a single case and a cross-case method operating on a population of cases are compatible and can be combined in empirical research. There is a need to reflect on whether and how set-theoretic MMR is internally coherent and how QCA and process tracing can be integrated in

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47

Ingo, Rohlfing, and Q. Schneider Carsten. "A Unifying Framework for Causal Analysis in Set-Theoretic Multimethod Research." Sociological Methods & Research 47, no. 1 (2021): 37–63. https://doi.org/10.5281/zenodo.4589193.

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Анотація:

The combination of Qualitative Comparative Analysis (QCA) with process tracing, which we call set-theoretic multimethod research (MMR), is steadily becoming more popular in empirical research. Despite the fact that both methods have an elected affinity based on set theory, it is not obvious how a within-case method operating in a single case and a cross-case method operating on a population of cases are compatible and can be combined in empirical research. There is a need to reflect on whether and how set-theoretic MMR is internally coherent and how QCA and process tracing can be integrated in

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48

Eichhorn, Astrid, Sumati Surya, and Fleur Versteegen. "Spectral dimension on spatial hypersurfaces in causal set quantum gravity." Classical and Quantum Gravity 36, no. 23 (2019): 235013. http://dx.doi.org/10.1088/1361-6382/ab47cd.

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49

Sorkin, Rafael D. "Scalar Field Theory on a Causal Set in Histories form." Journal of Physics: Conference Series 306 (July 8, 2011): 012017. http://dx.doi.org/10.1088/1742-6596/306/1/012017.

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50

Henson, Joe. "Constructing an interval of Minkowski space from a causal set." Classical and Quantum Gravity 23, no. 4 (2006): L29—L35. http://dx.doi.org/10.1088/0264-9381/23/4/l02.

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