Balcázar J.L., Días J. and Gabarró J. (1990). Structural Complexity I, 2nd edition, Springer-Verlag.

Beggs E., Costa J.F., Loff B. and Tucker J.V. (2008). Computational complexity with experiments as oracles. Proceedings of the Royal Society, Series A (Mathematical, Physical and Engineering Sciences)
464 (2098) 2777–2801.

Beggs E., Costa J.C., Loff B. and Tucker J.V. (2009). Computational complexity with experiments as oracles II. Upper bounds. Proceedings of the Royal Society, Series A (Mathematical, Physical and Engineering Sciences)
465 (2105) 1453–1465.

Beggs E., Costa J.F., Poças D. and Tucker J.V. (2013a). On the power of threshold measurements as oracles. In: Mauri G., Dennunzio A., Manzoni L. and Porreca A.E. (eds.) Unconventional Computation and Natural Computation (UCNC 2013), Lecture Notes in Computer Science, volume 7956, Springer-Verlag, 6–18.

Beggs E., Costa J.F., Poças D. and Tucker J.V. (2013b). Oracles that measure thresholds: The turing machine and the broken balance. Journal of Logic and Computation
23
(6)
1155–1181.

Beggs E., Costa J.F. and Tucker J.V. (2010a). Computational models of measurement and Hempel's axiomatization. In: Carsetti A. (ed.) Causality, Meaningful Complexity and Knowledge Construction, Theory and Decision Library A, volume 46, Springer-Verlag, 155–184.

Beggs E., Costa J.F. and Tucker J.V. (2010b). Limits to measurement in experiments governed by algorithms. Mathematical Structures in Computer Science
20
(06)
1019–1050. Special issue on Quantum Algorithms, editor Salvador Elías Venegas-Andraca.

Beggs E., Costa J.F. and Tucker J.V. (2010c). Physical oracles: The Turing machine and the Wheatstone bridge. Studia Logica
95
(1–2)
279–300. Special issue on Contributions of Logic to the Foundations of Physics, editors D. Aerts, S. Smets & J. P. Van Bendegem.

Beggs E., Costa J.F. and Tucker J.V. (2010d). The Turing machine and the uncertainty in the measurement process. In: Guerra H. (ed.) Physics and Computation, P&C 2010, CMATI – Centre for Applied Mathematics and Information Technology, University of Azores, 62–72.

Beggs E., Costa J.F. and Tucker J.V. (2012a). Axiomatising physical experiments as oracles to algorithms. Philosophical Transactions of the Royal Society, Series A (Mathematical, Physical and Engineering Sciences)
370
(12)
3359–3384.

Beggs E., Costa J.F. and Tucker J.V. (2012b). The impact of models of a physical oracle on computational power. Mathematical Structures in Computer Science
22
(5)
853–879. Special issue on Computability of the Physical, editors Cristian S. Calude and S. Barry Cooper.

Beggs E., Costa J.F. and Tucker J.V. (2014). Three forms of physical measurement and their computability. Reviews of Symbolic Logic
7
(4)
618–646.

Beggs E. and Tucker J.V. (2006). Embedding infinitely parallel computation in Newtonian kinematics. Applied Mathematics and Computation
178
(1)
25–43.

Beggs E. and Tucker J.V. (2007a). Can Newtonian systems, bounded in space, time, mass and energy compute all functions?
Theoretical Computer Science
371
(1)
4–19.

Beggs E. and Tucker J.V. (2007b). Experimental computation of real numbers by Newtonian machines. Proceedings of the Royal Society, Series A (Mathematical, Physical and Engineering Sciences)
463 (2082) 1541–1561.

Bekey G.A. and Karplus W.J. (1968). Hybrid Computation, John Wiley & Sons.

Born M. and Wolf E. (1964). Principles of Optics. Electromagnetic Theory of Propagation, Interference and Diffraction of Light, second (revised) edition, Pergamon Press.

Bournez O. and Cosnard M. (1996). On the computational power of dynamical systems and hybrid systems. Theoretical Computer Science
168
(2)
417–459.

Carnap R. (1966). Philosophical Foundations of Physics, Basic Books.

Geroch R. and Hartle J.B. (1986). Computability and physical theories. Foundations of Physics
16
(6)
533–550.

Hempel C.G. (1952). Fundamentals of concept formation in empirical science. International Encyclopedia of Unified Science, volume 2 no. 7, Chicago Univ. Press.

Krantz D.H., Suppes P., DuncanAAAALuce R. and Tversky A. (1990). Foundations of Measurement, vol. 1 (1971), vol. 2 (1989) and vol. 3 (1990), Academic Press.

Kreisel G. (1974). A notion of mechanistic theory. Synthese
29
(1)
11–26.

Pauly A. (2009). Representing measurement results. Journal of Universal Computer Science
15
(6)
1280–1300.

Pauly A. and Ziegler M. (2013). Relative computability and uniform continuity of relations. Journal of Logic and Analysis
5
(7)
139.

Pour-El M. (1974). Abstract computability and its relations to the general purpose analog computer. Transactions of the American Mathematical Society
199
1–28.

Pour-El M. and Richards I. (1979). A computable ordinary differential equation which possesses no computable solution. Annals of Mathematical Logic
17
(1–2)
61–90.

Pour-El M. and Richards I. (1981). The wave equation with computable initial data such that its unique solution is not computable. Advances in Mathematics
39
(4)
215–239.

Pour-El M. and Richards I. (1989). Computability in Analysis and Physics, Perspectives in Mathematical Logic, Springer-Verlag.

Siegelmann H.T. and Sontag E.D. (1994). Analog computation via neural networks. Theoretical Computer Science
131
(2)
331–360.

Weihrauch K. (2000). Computable Analysis, Springer-Verlag.

Weihrauch K. and Zhong N. (2002). Is wave propagation computable or can wave computers beat the Turing machine?
Proceedings of the London Mathematical Society
85
(2)
312–332.

Woods D. and Naughton T.J. (2005). An optical model of computation. Theoretical Computer Science
334
(1–3)
227–258.

Ziegler M. (2009). Physically-relativized Church-Turing hypotheses: Physical foundations of computing and complexity theory of computational physics. Applied Mathematics and Computation
215
(4)
1431–1447.