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Understanding causality is fundamental to science and inspires wide-ranging applications, yet there are several distinct notions of causation. Recently, there have been important developments on the role of causality in quantum physics, relativistic physics and their interplay. These have unearthed a plethora of fascinating open questions regarding the nature of causation, emergence of space-time structure and the limits of quantum information processing. At the same time, causal reasoning has become an important tool in machine learning and statistics, with applications ranging from big data to healthcare. This conference brings together experts from different areas of physics working on questions related to causality, as well as selected researchers who bridge the gap between fundamental research and current industrial applications. The aim of the conference is to provide a venue for cross-pollination of these ideas through scientific exchange between these communities. The conference will focus on the following facets of causality:
• Quantum and classical causal inference
• Indefinite causal order and quantum reference frames
• Causality in quantum field theory and quantum gravity
• Experiments and applications of causality
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Prospective speakers can submit a paper for a contributed talk (in person or online) and/or a poster (in person only) via the Call for Abstracts. The Call for Abstracts is now open! Submissions for a talk will automatically be considered for a poster if not accepted for a talk.
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Invited Speakers
Jessica Bavaresco (University of Geneva)
Cyril Branciard (CNRS, University Grenoble Alpes)
Rafael Chaves (Federal University of Rio Grande do Norte)
Giulio Chiribella (The University of Hong Kong)
Doreen Fraser (University of Waterloo)
Anne-Catherine de la Hamette (IQOQI Vienna)
Ciarán Lee (Spotify)
Tein van der Lugt (University of Oxford)
Joris M. Mooij (University of Amsterdam)
Mio Murao (University of Tokyo)
Alejandro Pozas-Kerstjens (University of Geneva)
Huw Price (Trinity College, Cambridge)
Renato Renner (ETH Zürich)
Thomas Richardson (University of Washington)
Sally Shrapnel (The University of Queensland)
Sumati Surya (Raman Research Institute)
Rainer Verch (University of Leipzig)
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Programme Committee
V Vilasini (ETH Zürich & Inria, University Grenoble Alpes) (PC Chair)
Augustin Vanrietvelde (Télécom Paris) (PC Co-chair)
Alastair Abbott (Inria, University Grenoble Alpes)
Časlav Brukner (IQOQI Vienna & University of Vienna)
Eric Cavalcanti (Griffith University)
Chris Fewster (University of York)
Lucien Hardy (Perimeter Institute)
Hlér Kristjánsson (Perimeter Institute & IQC & Université de Montréal)
Giulia Rubino (University of Bristol)
Nitica Sakharwade (Università degli Studi di Napoli Federico II)
Robert Spekkens (Perimeter Institute)
Jacopo Surace (Perimeter Institute)
Elie Wolfe (Perimeter Institute)
Lin-Qing Chen (ETH Zürich & IQOQI Vienna)
Hippolyte Dourdent (ICFO Barcelona)
Tamal Guha (University of Hong Kong)
Robin Lorenz (Quantinuum, Oxford)
Maria Papageorgiou (IQOQI Vienna)
Nicola Pinzani (Université libre de Bruxelles)
Marco-Túlio Quintino (Sorbonne Université, Paris)
Marc-Olivier Renou (Inria Paris-Saclay & CPHT, École polytechnique)
David Schmid (ICTQT, University of Gdańsk)
John Selby (ICTQT, University of Gdańsk)
Akihito Soeda (National Institute of Informatics, Tokyo)
Matthew Wilson (University College London)
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Scientific Organizers
Hlér Kristjánsson (Perimeter Institute & IQC & Université de Montréal) (Chair)
V Vilasini (ETH Zürich & Inria, University Grenoble Alpes)
Robert Spekkens (Perimeter Institute)
Lucien Hardy (Perimeter Institute)
Elie Wolfe (Perimeter Institute)
Jacopo Surace (Perimeter Institute)
Marina Maciel Ansanelli (Perimeter Institute)
Yìlè Yīng (Perimeter Institute)
María Ciudad Alañón (Perimeter Institute)
Daniel Centeno Díaz (Perimeter Institute)
Khushi Gandhi (Perimeter Institute & University of Waterloo)
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Previous editions:
Causalworlds 2022: The interface between quantum and relativistic causality, foundations and practicalities
Organised at ETH Zürich in 2022. Website: https://causalworlds.ethz.ch/"
Can the effectiveness of a medical treatment be determined without the expense of a randomized controlled trial? Can the impact of a new policy be disentangled from other factors that happen to vary at the same time? Questions such as these are the purview of the field of causal inference, a general-purpose science of cause and effect, applicable in domains ranging from epidemiology to economics. Researchers in this field seek in particular to find techniques for extracting causal conclusions from statistical data. Meanwhile, one of the most significant results in the foundations of quantum theory—Bell’s theorem—can also be understood as an attempt to disentangle correlation and causation. Recently, it has been recognized that Bell’s result is an early foray into the field of causal inference and that the insights derived from almost 60 years of research on his theorem can supplement and improve upon state-of-the-art causal inference techniques. In the other direction, the conceptual framework developed by causal inference researchers provides a fruitful new perspective on what could possibly count as a satisfactory causal explanation of the quantum correlations observed in Bell experiments. Efforts to elaborate upon these connections have led to an exciting flow of techniques and insights across the disciplinary divide. This tutorial will highlight some of what is happening at the intersection of these two fields.
In the Statistics literature there are three main frameworks for causal modeling: counterfactuals (aka potential outcomes), non-parametric structural equation models (NPSEMs) and graphs (aka path diagrams or causal Bayes nets). These approaches are similar and, in certain specific respects, equivalent. However, there are important conceptual differences and each formulation has its own strengths and weaknesses. These divergences are of relevance both in theory and when the approaches are applied in practice. This talk will introduce the different frameworks, and describe, through examples, both the commonalities and dissimilarities. In particular, we will see that the “default” assumptions within these frameworks lead to different identification results when quantifying mediation and, more generally, path-specific effects.
Based on the immense popularity of causal Bayesian networks and structural causal models, one might expect that these representations are appropriate to describe the causal semantics of any real-world system, at least in principle. In this talk, I will argue that this is not the case, and motivate the study of more general causal modeling frameworks. In particular, I will discuss bipartite graphical causal models.
Real-world complex systems are often modelled by systems of equations with endogenous and independent exogenous random variables. Such models have a long tradition in physics and engineering. The structure of such systems of equations can be encoded by a bipartite graph, with variable and equation nodes that are adjacent if a variable appears in an equation. I will show how one can use Simon’s causal ordering algorithm and the Dulmage-Mendelsohn decomposition to derive a Markov property that states the conditional independence for (distributions of) solutions of the equations in terms of the bipartite graph. I will then show how this Markov property gives rise to a do-calculus for bipartite graphical causal models, providing these with a refined causal interpretation.
Recent advances in quantum foundations have unveiled the idea that the causal order between quantum events may not always be fixed or even well-defined, allowing for some form of indefinite quantum causality. This tutorial will introduce the key concepts and motivations behind this rapidly developing area of research. Focusing on one of the main frameworks developed to explore indefinite quantum causality—the process matrix formalism—I will present key theoretical results, highlight the potential of indefinite causal orders as a resource for quantum information processing, and discuss experimental implementations as well as the physical interpretation of indefinite causal structures.
At the fundamental level, the dynamics of quantum particles and fields is time-symmetric: their dynamical equations are invariant under inversion of the time coordinate, possibly in conjunction with the change of other physical properties, such as charge and parity. At the operational level, the time-symmetry of the fundamental equations implies that certain quantum devices are bidirectional, meaning that the role of their inputs and outputs can be exchanged. Here we characterize the largest set of operations that can in principle be implemented on bidirectional devices, and show that this set includes operations in which the role of the input and output ports of the given devices becomes indefinite. An example of such an operation, called the “quantum time flip,” achieves input-output indefiniteness by adding quantum control to the direction in which a single device is used. We show that quantum operations with indefinite input-output directions can in principle achieve information-theoretic advantages over all possible operations with definite time direction, and can lead to an exetremely strong form of indefinite causal order.
Higher-order transformations that act on a certain number of input quantum channels with an indefinite causal order, such as the quantum switch, cannot be described by standard quantum circuits that use the same number of calls of the input quantum channels. But could they be simulated, i.e., could their action on their input channels be deterministically reproduced, for all arbitrary inputs, by a quantum circuit that uses on a larger number of calls of the input channels? In this work, we prove that, when only one extra call of each input channel is available, the quantum switch cannot be simulated. We demonstrate the robustness of this result by showing that even when probabilistic and approximate simulations are considered, higher-order transformations that are close to the quantum switch can be at best simulated with a probability strictly less than one. This result stands in stark contrast with the known fact that, when the quantum switch acts exclusively on unitary channels, its action can be simulated. We also show other particular cases where a restricted simulation of the quantum switch is possible. Finally, we discuss the implications of our findings to the analysis of experiments based on the quantum switch.
Given the large number of proposed quantum machine learning (QML) algorithms, it is somewhat surprising that ideas from this field have not yet been extended to causal learning. While deep learning and generative machine learning models have taken centre stage in the industrial application of automated learning on classical data, it is nonetheless well known that these techniques don't reliably capture causal concepts, leading to significant performance vulnerabilities. Increasingly, classical ML experts are taking ideas from causal inference, a field traditionally limited to small data sets of low dimensionality, and injecting modern ML elements to create new algorithms that benefit from the best of both worlds. These hybrid classical approaches provide new opportunity to search for potential quantum advantage. In this talk I explore this new research direction and propose several new quantum algorithms for classical causal inference.
We propose that Bell correlations are explicable as a combination of (i) collider bias and (ii) a boundary constraint on the collider variable. We show that the proposal is valid for a special class of ('W-shaped') Bell experiments involving delayed-choice entanglement swapping, and argue that it can be extended to the ordinary ('V-shaped') case. The proposal requires no direct causal influence outside lightcones, and may hence offer a way to reconcile Bell nonlocality and relativity.
It is not explicitly obvious that relativity and quantum mechanics are consistent with each other. Extensive research has shown that quantum states are consistent with relativity, in that they do not allow for faster-than-light transferring of information. In contrast, much less research has been done in quantum measurements, and in fact, naive attempts to put together relativity and quantum measurements lead to signaling between space-like separated regions. In this talk I will describe how this same problem arises in non-relativistic quantum physics, where measurements on systems kept spatially separated in general lead to signalling. By giving away the projection postulate, it is possible to alleviate this problem and measure non-local variables without signaling by exploiting pre-shared entanglement as a resource. I will describe a protocol for implementing any joint measurement in a non-signaling manner, and argue that this leads to a complete classification of all joint quantum measurements, based on the required amount of entanglement necessary to measure them.
Causal reasoning is vital for effective reasoning in many domains, from healthcare to economics. In medical diagnosis, for example, a doctor aims to explain a patient’s symptoms by determining the diseases causing them. This is because causal relations, unlike correlations, allow one to reason about the consequences of possible treatments and to answer counterfactual queries. In this talk I will present some recent work done with my collaborators about how one can learn and reason with counterfactual distributions, and why this is importantly for decision making. In all cases I will strive to motivate and contextualise the results with real word examples.
There are several non-causal effects that have been attributed to quantum physics. These include the analogues of "closed timelike curve effects" in quantum circuits proposed by David Deutsch (D-CTC), and the "impossible measurements" in relativistic quantum field theory discussed by Raphael Sorkin. Based on previous work, it will be pointed out in the talk that the alleged non-causality features arise not only in quantum systems, but in the very same manner in systems that are described in the framework of classical (non-quantum) statistical mechanics or classical field theory. Therefore, although the said non-causality scenarios have been portrayed as pertaining to quantum systems or quantum fields, they are in fact not based on, nor characteristic of, the quantum nature of physical systems.
The notion of causality is intimately tied to both, a transitive ordering on events, and the possibility of unrelated events. Thus, any causality structure is a partially ordered set or poset. This is the case in Lorentzian spacetime, which possesses a single time direction. In causal set quantum gravity, this spacetime causality structure is "first quantised" by discretising it. However, as with any dynamical quantum theory of spacetime, background notions of causality are insufficient. I will discuss how ordering and discreteness, as manifested in the sequential growth paradigm, provide a broad framework for quantum dynamical notions of causality.
In QFT, one aspect of relativistic causality is the principle of microcausality, which requires that observables associated with spacelike separated regions commute. But this principle is not by itself sufficient to rule out superluminal signalling, as examples of ‘impossible’ measurements demonstrate. Representations of the dynamics that respect relativity also play a necessary role in upholding relativistic causality in QFT. This talk will focus on the important role that principles of relativistic dynamics play in representations of local measurement in QFT.
Generalizations of Bell's theorem, particularly within quantum networks, are now being analyzed through the causal inference lens. However, the use of interventions, a central concept in causality theory, remains unexplored. As will be discussed, if we are not limited to observational data and can intervene in our experimental setup, we can witness quantum violations of classical causal bounds even when no Bell-like violation is possible. Through interventions, the quantum behavior of a system, that would seem classical otherwise, can be demonstrated. We will then present a photonic experiment implementing those ideas and consider applications of this framework for measurement-based quantum computation, quantification of causality in quantum gates and quantum network protocols.
Supermaps are higher-order transformations that take maps as input. We explore quantum algorithms that implement supermaps of unitary operations using multiple calls to a black-box unitary operation. We investigate how the causal structure and spacetime symmetry of these unitary black-boxes affect their performance in implementing higher-order quantum operations. We analyze several tasks, inversion, complex conjugation, and transposition of black-box unitaries.
Multipartite quantum channels realisable in a spacetime obey the no-superluminal-signalling constraints imposed by relativistic causality. But what about the converse: Can every channel that exhibits no superluminal signalling also be realised through relativistically valid dynamics? To our knowledge, only special cases of this question have been studied. For bipartite channels, the answer has been found to be negative in general (Beckman et al., 2001), though we will argue that counterexamples must necessarily involve a form of fine-tuning. Another special case of the question has been extensively explored under the name of nonlocal quantum computation in the context of position-based cryptography. We will pose and motivate the question in generality, conjecture a positive answer for all but the fine-tuned channels, and present results towards proving it, drawing on insights from nonlocal quantum computation and the new field of causally faithful circuit decompositions of unitary transformations (see also Tuesday). Beyond their relevance to spacetime realisability, the circuit decompositions involved in addressing the question also find applications in quantum causal modelling.
Recent research on quantum reference frames (QRFs) has shown that whether a system is in a superposed state of locations, momenta, and other properties can depend on the quantum reference frame relative to which it is being described. Whether an event is localized in spacetime or not can change under QRF transformations, in that case so-called quantum-controlled diffeomorphisms. This raises a critical question: can quantum reference frame transformations render indefinite causal order definite? In this talk, I propose a relativistic definition of causal order based on worldline coincidences and proper time differences, establishing it as an operationally meaningful observable in both general relativity and quantum mechanics. Using this definition, we can analyse the indefiniteness of causal order in the optical and gravitational quantum switch on equal footing. This analysis suggests an operational rather than a spacetime-based understanding of events. I will compare these findings to other recent results and conclude with broader implications for events in non-classical contexts
Causality is a core concept in both General Relativity (GR) and Quantum Information Theory (QIT), yet it manifests differently in each domain. In GR, causal cones appear as a defining property of spacetime. Conversely, in QIT, causality relates to the abstract flow of information in quantum processes, independent of spacetime. This raises a crucial question: under what conditions can an abstract quantum process be realised within spacetime? The question is especially intriguing for quantum processes with indefinite causal structure, like the Quantum Switch, which resist classical causal descriptions. In this talk, I will present no-go theorems that reveal fundamental limitations on the realisability of such processes in spacetime and, thus, more generally, on the interplay between GR and QIT. This is based on joint work with V. Vilasini (Physical Review Letters, 133 080201, 2024).