On Philosophy of Scientific
Experimentation
(PSX 4 Conference:
“No experiment result without
simulation”)
19 June 2014
V. Pronskikh
Fermilab
Outline
• Some history (introduction)
• Central questions (Hot topics) (PSX)
• Positions including examples from Philosophy
of Scientific Experimentation Conference 4
(PSX4), April 28-30, 2014, Pittsburgh
• (in red: my silly questions)
Experiment in antiquity and modernity
• Natural sciences (physics) are experimental.
• What are differences between experiment in
Modern Times and that in antiquity and Middle
Ages ?
• Empiricism – reality is the perfect natural order of
things, harmonious Cosmos. (Aristotle,
scholasticism). Thinking extracts theory from
empiric. Non-interference in the natural course of
things.
• Modern Times – not Cosmos or Nature but
separate phenomena are at the center of
attention
Experiment since Modern Times
• Separate phenomena, objects or processes
delaminated from the natural background and
transferred to the laboratory, where they can be
exposed to various influences – experimental
investigation of a phenomenon
• Falling bodies (Galileo), water flow in a channel
(Bernoulli), charge interactions ( Coulomb, Ampere).
• Three parts:
– Preparation of object (state)
– Phenomenon (theory or exploratory)
– Measurement of a phenomenon
Some history of the field
• P. Duhem, 1906. The Aim and Structure of Physical
Theory.
• I. Hacking, 1983, “Representing and Intervening,
Introductory Topics in the Philosophy of Natural Science”
• 1980s. A. Franklin “The Neglect of Experiment”, P.
Galison, A. Pickering
• 2003 “The Philosophy of Scientific Experimentation” ed.
H. Radder (G. Hon, M. Heidelberger, R. Harre, J.
Woodward, …)
• 2010s. “Epistemology at LHC” project, Wuppertal,
Germany
• Philosophy of Scientific Experimentation (PSX)
Conferences, A. Franklin
Questions (PSX): What makes good
experiment ?
• What roles experiment plays besides testing theories
(search for new phenomena) ?
• Can experiment be independent of theory ?
• What epistemic strategies experimentalists use to ensure
that their results are correct ?
• What are similarities and differences between
experiments in different sciences ?
• Are new phenomena discovered or created in laboratory ?
• Are there differences between experimental and
observational knowledge ?
• Are computer simulations theory or experiment ? What
role they play in experiments ?
Experiment and theory
• Goal of experiment – creation of a phenomenal
theory. Can precede theory.
• If the phenomenon cannot be brought in laboratory
(stars) – observation: selection instead of
preparation.
• In contemporary experiment: data analysis is part of
measurement
• Integrity of phenomenon and its theory in
experiment
• Example: Cosmic Microwave Background. Penzias,
Wilson, 1965. Excess 3.5 K temperature.
• Meaning was realized only after the theory was
found. (Gamow, 1948; Alpher, Herman, 1948)
Ladenness with instrumental theories
• P. Duhem, Discussed experiments on compressibility of
gases. Expanding gas displaced liquid in a pipe. The level of
liquid was used as indicator. Experimenters observed
displacement of fluid level and made conclusions about
temperature change.
• I. Hacking, studies of parity violations in weak interactions,
scientists scattered of electrons on deuterium, use of
electron gun, “not a theoretical process”
• Generalized scheme of experiment:
•
<P(T1…)|T(Ph)|M(T2…)>
• P – preparation, M – measurement, T(Ph) –
phenomenal theory, T1, T2… - instrumental theories
Epistemic Strategies in Experiment
• A. Franklin (PSX, Stanford Encyclopedia)
• Manipulating in a known way (adding ink) and observing
the predicted response (I.Hacking, if we can manipulate it
is real), reproducing known phenomena. Calibration.
• Independent confirmation using different apparatuses
(Radder, replicability). (see PSX 4 discussion)
• Impossibility to eliminate effect varying instrumental
procedure (Galison)
• Consistency of results (Kepler’s law)
• Using instruments based on well-corroborated theories
• Exclusion of sources of errors and alternative explanations
• Using statistical criteria
Is Replicability a Principle of Inductive
Logic ?
• PSX 4 (J. Norton)
• A project to justify that there are no universal principles of
inductive logic or schemes of inductive inference similar to
deductive one. It should be supported by local facts.
• Thesis: common in experimental sciences requirement of
reproducibility of experimental result cannot be reduced to
a principle of inductive logic. Discussed several examples
when either reproducibility was not epistemically
significant or its absence was inert.
• His explanation: “background facts” are sufficient to
support reliability of experimental results.
• Are they always sufficient ?
Simulations are experiments
• (PSX 4) E. Parke
• Do experiments have epistemic privilege over simulations? Can
simulations surprise us like experiments can ?
• Thesis: surprise claim is false as generalization (sometimes they
can). Two reasons:
• Unexpected behaviour (exhibit surprising states or phenomena)
(using model not she wrote, high-level languages, highly complex
models written by teams). P. Humphreys (epistemic opacity of
simulations). These are computer simulations.
• Hidden mechanisms or causal factors. Discovery of transposable
genetic elements in the course of genome studies. These are
agent-based simulations. Surprise is productive, but valid
scientific inferences are possible only if we eliminate sources of
surprise.
• Is there a way to prove agent-based simulation has no surprises?
Can, say, animal models always be used reliably?
Calibration of animal models
• (PSX 4) N. Atanasova
• Thesis: Experimental modeling in neurobiology employs
calibrating animal models to establish validity of claims about
relevant human conditions.
• Different experimental protocols in neurobiology produce
different laboratory effects. Assumption that they correspond to
identical world phenomena is not justified. Validity and
reliability trade off. Local validity of models.
• Calibration: 1) animal models against multiple factors to
reproduce known effects; 2) different animal models are crosschecked to produce compatible results; 3) identical animal
models are tested in different laboratories.
• Thesis: integration of converging results produces knowledge
that extends further than each individual laboratory context.
• Fowl chick model of anxiety depression.
• How further? How about hidden mechanisms and causal
factors?
Simulation, Experiments, and
Validation Experiments
• (PSX 4) M. Morrison. Thesis: there is no experimental result
without simulation
• The basis of distinction between experimentation and
simulation is materiality (for computer simulations).
• Studies the role of simulation in the Higgs searches at the LHC.
ATLAS and CMS: reliance on simulation undermines the sharp
division between simulation and experimentation.
• How to establish legitimacy of simulation: verification of
algorithms is not enough, extensive validation experiments are
required for the accuracy of simulation. (also, Oberkampf,
2004). Simulations are part of experimentation. Interplay
between experimentation and simulation, simulations are
necessary.
• Does interplay always entail necessity? (example: summer and
mosquitoes)
Some other topics shortly
• N.M. Boyd, Equivalence principle tests. The results support
the geometric interpretation of gravity. Relation between
theory and experiment should be made explicit.
• C. Craver, Thinking about interventions. Experiments to
intervene in brain functions. Many examples.
• K. Creel, Machine Learning as Experiment. Machine
learning can help discover new phenomena (search in data
sets).
• M. Fagan, Crucial stem cell experiments ? Empirical claims
about stem cells are uncertain (concept features and
general facts about experiments in stem cell biology).
• P. Grabowski, Perspectives on RNA. “Biologist is part of
biology”.
• I. Meketa, How parsimony Biases Experimental Design in
Comparative Cognition. As the simplicity is an epistemic
virtue scientists seek simpler models.
Conclusion
• The PSX 4 Conference was productive and
successful (thanks to chair Prof. A. Franklin,
the discussion moderator Dr. S. Perovic, and
the Organizing Committee).
• Many topics were discussed, many answers,
and many more questions remain.
• Thank you for your patience.