Nuclear arms control: optimising verification processes through formal modelling
Paul Beaumont
10.17862/cranfield.rd.4288850.v2
https://cord.cranfield.ac.uk/articles/dataset/Nuclear_arms_control_optimising_verification_processes_through_formal_modelling/4288850
<p>Technical paper presented at the 2016 Defence and Security Doctoral Symposium.</p><p>Arms
control verification processes do not in practice allow for the parties
involved to gather complete information about each other. Instead, each must
make decisions about whether or not other parties are complying with their
obligations on the basis of limited information. They must also make decisions
during negotiation of a verification regime about the measures to be used, and
during implementation of that regime about how and when to use the tools at
their disposal. Decision-making under uncertainty is therefore a core element
of the arms control verification problem. Our work aims to extend and combine
mathematical modelling and verification approaches such that they can cope with
the inherent lack of available data in this domain, and potentially be used to
support policy-makers in practice. </p>
<p>Our approach is to model the
beliefs of each party and the various inspection control processes in a type of
software known as a Satisfiability Modulo Theories (SMT) solver. This offers a
general purpose approach to the automated analysis of mathematical models; in
our case we use SMT to deal with uncertainty in (or absence of) data by
expressing them as under-specifications of parameters in model verification
processes. In other words, we don’t have to choose values for parameters
– such as the number of nuclear weapons that one of the parties holds, for
example – if we don’t know them: we can pick a range of possible values, or
leave the value totally unconstrained.</p>
<p>We demonstrate
the capabilities of this approach by exploring a representative, quantitative
model of an arms control process in which two parties engage in mutual nuclear
arms reduction and verification activities. We show that we are able to answer
pertinent questions such as “given uncertainty in our treaty partners’ initial
weapon stockpile, with scheduled inspections every 6 months and 2 other
unscheduled inspections per year, what timing for unscheduled inspections leads
to the minimum difference between our partners’ declaration and our assessment
of their actual arsenal?”</p>
<p>These
new modelling and analysis methods allow for a much more sophisticated approach
to modelling arms control: we have harnessed a supercomputer to analyse over
134 million possible inspection timelines, allowing the software to compute an
inspection schedule over a treaty lifespan of 2 years for which performance
against one or more measures of interest is optimised. The models and results
can then be studied and their expected outcomes assessed to assist in
decision-making regarding proposed arms control regimes.</p>
<p><b> </b></p>
<p><b>Biographical
Notes:</b></p>
<p><b>Paul Beaumont </b>is a final year
Postgraduate Research student in the Department of Computing at Imperial
College London. His PhD focusses on understanding and solving mathematical
models in the absence of data, and follows on from a Masters and undergraduate
in Mathematics, also at Imperial. He works with colleagues from AWE and is
applying his PhD techniques to the problem of nuclear arms verification.</p>
2016-12-09 11:15:41
Verification
Modelling
Arms control
DSDS16 technical paper
DSDS16
Mathematical Sciences not elsewhere classified