Broadly speaking, the contemporary scientific realist is concerned to justify belief in what we might call theoretical truth, which includes truth based on ampliative inference and truth about unobservables. Many, if not most, contemporary realists say scientific realism should be treated as ‘an overarching scientific hypothesis’ (Putnam 1978, p. 18). In its most basic form, the realist hypothesis states that theories enjoying general predictive success are true. This hypothesis becomes a hypothesis to be tested. To justify our belief in the (...) realist hypothesis, realists commonly put forward an argument known as the ‘no-miracles argument’. With respect to the basic hypothesis this argument can be stated as follows: it would be a miracle were our theories as successful as they are, were they not true; the only possible explanation for the general predictive success of our scientific theories is that they are true. (shrink)

For many years—and with some energy since Laudan’s “Confutation of Convergent Realism” —the scientific realist has sought to accommodate examples of false-yet-successful theories in the history of science. One of the most prominent strategies is to identify ‘success fueling’ components of false theories that themselves are at least approximately true. In this article I develop both sides of the debate, introducing new challenges from the history of science as well as suggesting adjustments to the divide et impera realist strategy. A (...) new ‘recipe’ for the prospective identification of working/idle posits is considered. (shrink)

Recent experiments have shown that certain fluid-mechanical systems, namely oil droplets bouncing on oil films, can mimic a wide range of quantum phenomena, including double-slit interference, quantization of angular momentum and Zeeman splitting. Here I investigate what can be learned from these systems concerning no-go theorems as those of Bell and Kochen-Specker. In particular, a model for the Bell experiment is proposed that includes variables describing a ‘background’ field or medium. This field mimics the surface wave that accompanies the droplets (...) in the fluid-mechanical experiments. It appears that quite generally such a model can violate the Bell inequality and reproduce the quantum statistics, even if it is based on local dynamics only. The reason is that measurement independence is not valid in such models. This opens the door for local ‘background-based’ theories, describing the interaction of particles and analyzers with a background field, to complete quantum mechanics. Experiments to test these ideas are also proposed. (shrink)

This paper defends an inferential conception of scientific representation. It approaches the notion of representation in a deflationary spirit, and minimally characterizes the concept as it appears in science by means of two necessary conditions: its essential directionality and its capacity to allow surrogate reasoning and inference. The conception is defended by showing that it successfully meets the objections that make its competitors, such as isomorphism and similarity, untenable. In addition the inferential conception captures the objectivity of the cognitive representations (...) used by science, it sheds light on their truth and completeness, and it explains the source of the analogy between scientific and artistic modes of representation. (shrink)

Toy models are highly idealized and extremely simple models. Although they are omnipresent across scientific disciplines, toy models are a surprisingly under-appreciated subject in the philosophy of science. The main philosophical puzzle regarding toy models concerns what the epistemic goal of toy modelling is. One promising proposal for answering this question is the claim that the epistemic goal of toy models is to provide individual scientists with understanding. The aim of this article is to precisely articulate and to defend this (...) claim. In particular, we will distinguish between autonomous and embedded toy models, and then argue that important examples of autonomous toy models are sometimes best interpreted to provide how-possibly understanding, while embedded toy models yield how-actually understanding, if certain conditions are satisfied. _1_ Introduction _2_ Embedded and Autonomous Toy Models _2.1_ Embedded toy models _2.2_ Autonomous toy models _2.3_ Qualification _3_ A Theory of Understanding for Toy Models _3.1_ Preliminaries and requirements _3.2_ The refined simple view _4_ Two Kinds of Understanding with Toy Models _4.1_ Embedded toy models and how-actually understanding _4.2_ Against a how-actually interpretation of all autonomous toy models _4.3_ The how-possibly interpretation of some autonomous toy models _5_ Conclusion. (shrink)

Toy models are highly idealized and extremely simple models. Although they are omnipresent across scientific disciplines, toy models are a surprisingly under-appreciated subject in the philosophy of science. The main philosophical puzzle regarding toy models is that it is an unsettled question what the epistemic goal of toy modeling is. One promising proposal for answering this question is the claim that the epistemic goal of toy models is to provide individual scientists with understanding. The aim of this paper is to (...) precisely articulate and to defend this claim. In particular, we will distinguish between autonomous and embedded toy models, and, then, argue that important examples of autonomous toy models are sometimes best interpreted to provide how-possibly understanding, while embedded toy models yield how-actually understanding, if certain conditions are satisfied. (shrink)

Philosophers of science have often favoured reductive approaches to how-possibly explanation. This article identifies three alternative conceptions making how-possibly explanation an interesting phenomenon in its own right. The first variety approaches “how possibly X?” by showing that X is not epistemically impossible. This can sometimes be achieved by removing misunderstandings concerning the implications of one’s current belief system but involves characteristically a modification of this belief system so that acceptance of X does not result in contradiction. The second variety offers (...) a potential how-explanation of X. It is usually followed by a range of further potential how-explanations of the same phenomenon. In recent literature the factual claims implied by the second variety have been downplayed whereas the heuristic role of mapping the space of conceptual possibilities has been emphasized. I will focus especially on this truth-bracketing sense of potentiality when looking closer at the second variety in the paper. The third variety has attracted less interest. It presents a partial how-explanation of X. Typically it aims to establish the existence of a mechanism by which X could be and was generated. The third conception stands out as the natural alternative for the advocate of ontic how-possibly explanations. This article transfers Salmon’s view that explanation-concepts can be broadly divided into epistemic, modal, and ontic to the context of how-possibly explanations. Moreover, it is argued that each of the three above-mentioned varieties of how-possibly explanation occurs in science. To recognize this may be especially relevant for philosophers. We are often misled by the promises of various why-explanation accounts, and seem to have forgotten nearly everything about the diversity of how-possibly explanations. (shrink)

In this paper I argue-against van Fraassen's constructive empiricism-that the practice of saving phenomena is much broader than usually thought, and includes unobservable phenomena as well as observable ones. My argument turns on the distinction between data and phenomena: I discuss how unobservable phenomena manifest themselves in data models and how theoretical models able to save them are chosen. I present a paradigmatic case study taken from the history of particle physics to illustrate my argument. The first aim of this (...) paper is to draw attention to the experimental practice of saving unobservable phenomena, which philosophers have overlooked for too long. The second aim is to explore some far-reaching implications this practice may have for the debate on scientific realism and constructive empiricism. (shrink)

Scientific realists have claimed that the posit that our theories are (approximately) true provides the best or the only explanation for their success . In response, I revive two non-realists explanations. I show that realists, in discarding them, have either misconstrued the phenomena to be explained or mischaracterized the relationship between these explanations and their own. I contend nonetheless that these non-realist competitors, as well as their realist counterparts, should be rejected; for none of them succeed in explaining a significant (...) list of successes. I propose a related non-realist explanation of success that appears to be the most suitable among those considered. (shrink)

Many biological investigations are organized around a small group of species, often referred to as ‘model organisms’, such as the fruit fly Drosophila melanogaster. The terms ‘model’ and ‘modelling’ also occur in biology in association with mathematical and mechanistic theorizing, as in the Lotka–Volterra model of predator-prey dynamics. What is the relation between theoretical models and model organisms? Are these models in the same sense? We offer an account on which the two practices are shown to have different epistemic characters. (...) Theoretical modelling is grounded in explicit and known analogies between model and target. By contrast, inferences from model organisms are empirical extrapolations. Often such extrapolation is based on shared ancestry, sometimes in conjunction with other empirical information. One implication is that such inferences are unique to biology, whereas theoretical models are common across many disciplines. We close by discussing the diversity of uses to which model organisms are put, suggesting how these relate to our overall account. 1 Introduction2 Volterra and Theoretical Modelling3 Drosophila as a Model Organism4 Generalizing from Work on Model Organisms5 Phylogenetic Inference and Model Organisms6 Further Roles of Model Organisms6.1 Preparative experimentation6.2 Model organisms as paradigms6.3 Model organisms as theoretical models6.4 Inspiration for engineers6.5 Anchoring a research community7 Conclusion. (shrink)

This essay contains a partial exploration of some key concepts associated with the epistemology of realist philosophies of science. It shows that neither reference nor approximate truth will do the explanatory jobs that realists expect of them. Equally, several widely-held realist theses about the nature of inter-theoretic relations and scientific progress are scrutinized and found wanting. Finally, it is argued that the history of science, far from confirming scientific realism, decisively confutes several extant versions of avowedly 'naturalistic' forms of scientific (...) realism. (shrink)

A general account of modeling in physics is proposed. Modeling is shown to involve three components: denotation, demonstration, and interpretation. Elements of the physical world are denoted by elements of the model; the model possesses an internal dynamic that allows us to demonstrate theoretical conclusions; these in turn need to be interpreted if we are to make predictions. The DDI account can be readily extended in ways that correspond to different aspects of scientific practice.

Judea Pearl has been at the forefront of research in the burgeoning field of causal modeling, and Causality is the culmination of his work over the last dozen or so years. For philosophers of science with a serious interest in causal modeling, Causality is simply mandatory reading. Chapter 2, in particular, addresses many of the issues familiar from works such as Causation, Prediction and Search by Peter Spirtes, Clark Glymour, and Richard Scheines. But philosophers with a more general interest in (...) causation will also profit from reading Pearl’s book, especially the material in chapters 7, 9, and 10, which is self-contained and less technical than other parts of the book. The present review is aimed primarily at readers of the second type. (shrink)

Many scientific models are representations. Building on Goodman and Elgin’s notion of representation-as we analyse what this claim involves by providing a general definition of what makes something a scientific model, and formulating a novel account of how they represent. We call the result the DEKI account of representation, which offers a complex kind of representation involving an interplay of, denotation, exemplification, keying up of properties, and imputation. Throughout we focus on material models, and we illustrate our claims with the (...) Phillips-Newlyn machine. In the conclusion we suggest that, mutatis mutandis, the DEKI account can be carried over to other kinds of models, notably fictional and mathematical models. (shrink)

Confirmation in evolutionary biology depends on what biologists take to be the genuine rivals. Investigating what constrains the scope of biological possibility provides part of the story: explaining how possible helps determine what counts as a genuine rival and thus informs confirmation. To clarify the criteria for genuine rivalry I distinguish between global and local constraints on biological possibility, and offer an account of how-possibly explanation. To sharpen the connection between confirmation and explaining how possible I discuss the view that (...) formal inquiry can provide a kind of confirmation-theoretic support for evolutionary models, and offer an example of how-possibly explanation interacting with testing practice. (shrink)

Confirmation in evolutionary biology depends on what biologists take to be the genuine rivals. Investigating what constrains the scope of biological possibility provides part of the story: explaining how possible helps determine what counts as a genuine rival and thus informs confirmation. To clarify the criteria for genuine rivalry I distinguish between global and local constraints on biological possibility, and offer an account of how-possibly explanation. To sharpen the connection between confirmation and explaining how possible I discuss the view that (...) formal inquiry can provide a kind of confirmation-theoretic support for evolutionary models, and offer an example of how-possibly explanation interacting with testing practice. (shrink)

Certain hypotheses cannot be directly confirmed for theoretical, practical, or moral reasons. For some of these hypotheses, however, there might be a workaround: confirmation based on analogical reasoning. In this paper we take up Dardashti, Hartmann, Thébault, and Winsberg’s (in press) idea of analyzing confirmation based on analogical inference Baysian style. We identify three types of confirmation by analogy and show that Dardashti et al.’s approach can cover two of them. We then highlight possible problems with their model as a (...) general approach to analogical inference and argue that these problems can be avoided by supplementing Bayesian update with Jeffrey conditionalization. (shrink)

According to an argument by Colin Howson, the no-miracles argument is contingent on committing the base-rate fallacy and is therefore bound to fail. We demonstrate that Howson’s argument only applies to one of two versions of the NMA. The other version, which resembles the form in which the argument was initially presented by Putnam and Boyd, remains unaffected by his line of reasoning. We provide a formal reconstruction of that version of the NMA and show that it is valid. Finally, (...) we demonstrate that the use of subjective priors is consistent with the realist implication of the NMA and show that a core worry with respect to the suggested form of the NMA can be dispelled. (shrink)

We present a Bayesian analysis of the epistemology of analogue experiments with particular reference to Hawking radiation. Provided such experiments can be externally validated via universality arguments, we prove that they are confirmatory in Bayesian terms. We then provide a formal model for the scaling behaviour of the confirmation measure for multiple distinct realisations of the analogue system and isolate a generic saturation feature. Finally, we demonstrate that different potential analogue realisations could provide different levels of confirmation. Our results thus (...) provide a basis both to formalise the epistemic value of analogue experiments that have been conducted and to advise scientists as to the respective epistemic value of future analogue experiments. (shrink)

In this article we argue for the existence of ‘analogue simulation’ as a novel form of scientific inference with the potential to be confirmatory. This notion is distinct from the modes of analogical reasoning detailed in the literature, and draws inspiration from fluid dynamical ‘dumb hole’ analogues to gravitational black holes. For that case, which is considered in detail, we defend the claim that the phenomena of gravitational Hawking radiation could be confirmed in the case that its counterpart is detected (...) within experiments conducted on diverse realizations of the analogue model. A prospectus is given for further potential cases of analogue simulation in contemporary science. 1 Introduction2 Physical Background2.1 Hawking radiation in semi-classical gravity2.2 Modelling sound in fluids2.3 The acoustic analogue model of Hawking radiation3 Simulation and Analogy in Physical Theory3.1 Analogical reasoning and analogue simulation3.2 Confirmation via analogue simulation3.3 Recapitulation4 The Sound of Silence: Analogical Insights into Gravity4.1 Experimental realization of analogue models4.2 Universality and the Hawking effect4.3 Confirmation of gravitational Hawking radiation5 Prospectus. (shrink)

A primary goal of quantum computer science is to find an explanation for the fact that quantum computers are more powerful than classical computers. In this paper I argue that to answer this question is to compare algorithmic processes of various kinds and to describe the possibility spaces associated with these processes. By doing this, we explain how it is possible for one process to outperform its rival. Further, in this and similar examples little is gained in subsequently asking a (...) how-actually question. Once one has explained how-possibly, there is little left to do. (shrink)

Analogue experiments have attracted interest for their potential to shed light on inaccessible domains. For instance, ‘dumb holes’ in fluids and Bose–Einstein condensates, as analogues of black holes, have been promoted as means of confirming the existence of Hawking radiation in real black holes. We compare analogue experiments with other cases of experiment and simulation in physics. We argue—contra recent claims in the philosophical literature—that analogue experiments are not capable of confirming the existence of particular phenomena in inaccessible target systems. (...) As they must assume the physical adequacy of the modelling framework used to describe the inaccessible target system, arguments to the conclusion that analogue experiments can yield confirmation for phenomena in those target systems, such as Hawking radiation in black holes, beg the question. (shrink)

In this paper, I develop Mauricio Suárez’s distinction between denotation, epistemic representation, and faithful epistemic representation. I then outline an interpretational account of epistemic representation, according to which a vehicle represents a target for a certain user if and only if the user adopts an interpretation of the vehicle in terms of the target, which would allow them to perform valid (but not necessarily sound) surrogative inferences from the model to the system. The main difference between the interpretational conception I (...) defend here and Suárez’s inferential conception is that the interpretational account is a substantial account—interpretation is not just a “symptom” of representation; it is what makes something an epistemic representation of a something else. (shrink)

In this paper we study a classical and theoretical system which consists of an elastic medium carrying transverse waves and one point-like high elastic medium density, called concretion. We compute the equation of motion for the concretion as well as the wave equation of this system. Afterwards we always consider the case where the concretion is not the wave source any longer. Then the concretion obeys a general and covariant guidance formula, which leads in low-velocity approximation to an equivalent de (...) Broglie-Bohm guidance formula. The concretion moves then as if exists an equivalent quantum potential. A strictly equivalent free Schrödinger equation is retrieved, as well as the quantum stationary states in a linear or spherical cavity. We compute the energy of the concretion, naturally defined from the energy density of the vibrating elastic medium. Provided one condition about the amplitude of oscillation is fulfilled, it strikingly appears that the energy and momentum of the concretion not only are written in the same form as in quantum mechanics, but also encapsulate equivalent relativistic formulas. (shrink)

Simulations using idealized numerical models can often generate behaviors or patterns that are visually very similar to the natural phenomenon being investigated and to be explained. The question arises, when should these model simulations be taken to provide an explanation for why the natural phenomena exhibit the patterns that they do? An important distinction for answering this question is that between ‘how-possibly’ explanations and ‘how-actually’ explanations. Despite the importance of this distinction there has been surprisingly little agreement over how exactly (...) this distinction should bedrawn. I shall argue that inadequate attention has been paid to the different contexts in which an explanation can be given and the different levels of abstraction at which the explanandum phenomenon can be framed. By tracing how scientists are using model simulations to explain a striking periodic banding of vegetation known as tiger bush, I will show how our understanding of the distinction between how-possibly and how-actually model explanations needs to be revised. (shrink)

The question of where, between theory and experiment, computer simulations (CSs) locate on the methodological map is one of the central questions in the epistemology of simulation (cf. Saam Journal for General Philosophy of Science, 48, 293–309, 2017). The two extremes on the map have them either be a kind of experiment in their own right (e.g. Barberousse et al. Synthese, 169, 557–574, 2009; Morgan 2002, 2003, Journal of Economic Methodology, 12(2), 317–329, 2005; Morrison Philosophical Studies, 143, 33–57, 2009; Morrison (...) 2015; Massimi and Bhimji Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 51, 71–81, 2015; Parker Synthese, 169, 483–496, 2009) or just an argument executed with the aid of a computer (e.g. Beisbart European Journal for Philosophy of Science, 2, 395–434, 2012; Beisbart and Norton International Studies in the Philosophy of Science, 26, 403–422, 2012). There exist multiple versions of the first kind of position, whereas the latter is rather unified. I will argue that, while many claims about the ‘experimental’ status of CSs seem unjustified, there is a variant of the first position that seems preferable. In particular I will argue that while CSs respect the logic of (deductively valid) arguments, they neither agree with their pragmatics nor their epistemology. I will then lay out in what sense CSs can fruitfully be seen as experiments, and what features set them apart from traditional experiments nonetheless. I conclude that they should be seen as surrogate experiments, i.e. experiments executed consciously on the wrong kind of system, but with an exploitable connection to the system of interest. Finally, I contrast my view with that of Beisbart (European Journal for Philosophy of Science, 8, 171–204, 2018), according to which CSs are surrogates for experiments, arguing that this introduces an arbitrary split between CSs and other kinds of simulations. (shrink)

Both clinical research and basic science rely on the epistemic practice of extrapolation from surrogate models, to the point that explanatory accounts presented in review papers and biology textbooks are in fact composite pictures reconstituted from data gathered in a variety of distinct experimental setups. This raises two new challenges to previously proposed mechanistic-similarity solutions to the problem of extrapolation: one pertaining to the absence of mechanistic knowledge in the early stages of research and the second to the large number (...) of extrapolations underpinning explanatory accounts. An analysis of the strategies deployed in experimental research supports the conclusion that while results from validated surrogate models are treated as a legitimate line of evidence supporting claims about target systems, the overall structure of research projects also demonstrates that extrapolative inferences are not considered definitive or sufficient evidence, but only partially justified hypotheses subjected to further testing. 1 Introduction2 Surrogate Models2.1 What exactly is a surrogate model?2.2 Why use surrogate models?3 Prior Validation of Surrogate Models3.1 The validation and ranking of surrogate models in the early stages of basic research3.2 The validation of surrogate models in later stages of basic research and in clinical research4 ‘Big Picture’ Accounts and the Extrapolations Underpinning Them4.1 The mosaic nature of mechanistic descriptions in basic science4.2 Challenges for mechanistic-similarity-based validation protocols5 Retrospective Testing of Extrapolated Knowledge5.1 Holistic confirmation5.2 Fallback strategies6 Conclusions. (shrink)

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

Taking scientific practice as its starting point, this book charts the complex territory of models used in science. It examines what scientific models are and what their function is. Reliance on models is pervasive in science, and scientists often need to construct models in order to explain or predict anything of interest at all. The diversity of kinds of models one finds in science – ranging from toy models and scale models to theoretical and mathematical models – has attracted attention (...) not only from scientists, but also from philosophers, sociologists, and historians of science. This has given rise to a wide variety of case studies that look at the different uses to which models have been put in specific scientific contexts. By exploring current debates on the use and building of models via cutting-edge examples drawn from physics and biology, the book provides broad insight into the methodology of modelling in the natural sciences. It pairs specific arguments with introductory material relating to the ontology and the function of models, and provides some historical context to the debates as well as a sketch of general positions in the philosophy of scientific models in the process. (shrink)

Scientists have used models for hundreds of years as a means of describing phenomena and as a basis for further analogy. In Scientific Models in Philosophy of Science, Daniela Bailer-Jones assembles an original and comprehensive philosophical analysis of how models have been used and interpreted in both historical and contemporary contexts. Bailer-Jones delineates the many forms models can take (ranging from equations to animals; from physical objects to theoretical constructs), and how they are put to use. She examines early mechanical (...) models employed by nineteenth-century physicists such as Kelvin and Maxwell, describes their roots in the mathematical principles of Newton and others, and compares them to contemporary mechanistic approaches. Bailer-Jones then views the use of analogy in the late nineteenth century as a means of understanding models and to link different branches of science. She reveals how analogies can also be models themselves, or can help to create them. The first half of the twentieth century saw little mention of models in the literature of logical empiricism. Focusing primarily on theory, logical empiricists believed that models were of temporary importance, flawed, and awaiting correction. The later contesting of logical empiricism, particularly the hypothetico-deductive account of theories, by philosophers such as Mary Hesse, sparked a renewed interest in the importance of models during the 1950s that continues to this day. Bailer-Jones analyzes subsequent propositions of: models as metaphors; Kuhn's concept of a paradigm; the Semantic View of theories; and the case study approaches of Cartwright and Morrison, among others. She then engages current debates on topics such as phenomena versus data, the distinctions between models and theories, the concepts of representation and realism, and the discerning of falsities in models. (shrink)

one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

Introduction -- Sanctioning models : theories and their scope -- Methodology for a virtual world -- A tale of two methods -- When theories shake hands -- Models of climate : values and uncertainties -- Reliability without truth -- Conclusion.

The 1927 Solvay conference was perhaps the most important meeting in the history of quantum theory. Contrary to popular belief, the interpretation of quantum theory was not settled at this conference, and no consensus was reached. Instead, a range of sharply conflicting views were presented and extensively discussed, including de Broglie's pilot-wave theory, Born and Heisenberg's quantum mechanics, and Schrödinger's wave mechanics. Today, there is no longer an established or dominant interpretation of quantum theory, so it is important to re-evaluate (...) the historical sources and keep the interpretation debate open. This book contains a complete translation of the original proceedings, with background essays on the three main interpretations of quantum theory presented at the conference, and an extensive analysis of the lectures and discussions in the light of current research in the foundations of quantum theory. The proceedings contain much unexpected material, including extensive discussions of de Broglie's pilot-wave theory (which de Broglie presented for a many-body system), and a theory of 'quantum mechanics' apparently lacking in wave function collapse or fundamental time evolution. This book will be of interest to graduate students and researchers in physics and in the history and philosophy of quantum theory. (shrink)

This paper provides the first systematic philosophical analysis of an increasingly important part of modern scientific practice: analogue quantum simulation. We introduce the distinction between `simulation' and `emulation' as applied in the context of two case studies. Based upon this distinction, and building upon ideas from the recent philosophical literature on scientific understanding, we provide a normative framework to isolate and support the goals of scientists undertaking analogue quantum simulation and emulation. We expect our framework to be useful to both (...) working scientists and philosophers of science interested in cutting-edge scientific practice. (shrink)

Bellʼs 1964 theorem causes a severe problem for the notion that correlations require explanation, encapsulated in Reichenbachʼs principle of common cause. Despite being a hallmark of scientific thought, dropping the principle has been widely regarded as much less bitter medicine than the perceived alternative—dropping relativistic causality. Recently, however, some authors have proposed that modified forms of Reichenbachʼs principle could be maintained even with relativistic causality. Here we break down Reichenbachʼs principle into two independent assumptions—the principle of common cause proper and (...) factorization of probabilities. We show how Bellʼs theorem can be derived from these two assumptions plus relativistic causality and the law of total probability for actual events, and we review proposals to drop each of these assumptions in light of the theorem. In particular, we show that the non-commutative common causes of Hofer-Szabó and Vecsernyés fail to have an analogue of the notion that the common causes can explain the observed correlations. Moreover, we show that their definition can be satisfied trivially by any quantum product state for any quantum correlations. We also discuss how the conditional states approach of Leifer and Spekkens fares in this regard. (shrink)

In 1981 Unruh proposed that fluid mechanical experiments could be used to probe key aspects of the quantum phenomenology of black holes. In particular, he claimed that an analogue to Hawking radiation could be created within a fluid mechanical `dumb hole', with the event horizon replaced by a sonic horizon. Since then an entire sub-field of `analogue gravity' has been created. In 2016 Steinhauer reported the experimental observation of quantum Hawking radiation and its entanglement in a Bose-Einstein condensate analogue black (...) hole. What can we learn from such analogue experiments? In particular, in what sense can they provide evidence of novel phenomena such as black hole Hawking radiation? (shrink)

To demarcate the limits of experimental knowledge, we probe the limits of what might be called an experiment. By appeal to examples of scientific practice from astrophysics and analogue gravity, we demonstrate that the reliability of knowledge regarding certain phenomena gained from an experiment is not circumscribed by the manipulability or accessibility of the target phenomena. Rather, the limits of experimental knowledge are set by the extent to which strategies for what we call ‘inductive triangulation’ are available: that is, the (...) validation of the mode of inductive reasoning involved in the source-target inference via appeal to one or more distinct and independent modes of inductive reasoning. When such strategies are able to partially mitigate reasonable doubt, we can take a theory regarding the phenomena to be well supported by experiment. When such strategies are able to fully mitigate reasonable doubt, we can take a theory regarding the phenomena to be established by experiment. There are good reasons to expect the next generation of analogue experiments to provide genuine knowledge of unmanipulable and inaccessible phenomena such that the relevant theories can be understood as well supported. This article is part of a discussion meeting issue ‘The next generation of analogue gravity experiments’. (shrink)