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We propose a quantum circuit that emulates a delayed-choice quantum eraser via bipartite entanglement with the extension that the degree of entanglement between the two paired quantons is adjustable. This provides a broader setting to test…

Quantum Physics · Physics 2024-01-09 Dah-Wei Chiou , Hsiu-Chuan Hsu

The theory of decoherent histories is checked for the requirement of statistical independence of subsystems. Strikingly, this is satisfied only when the decoherence functional is diagonal in both its real a n d imaginary parts. In…

Quantum Physics · Physics 2009-11-10 Lajos Diosi

A PhD student is locked inside a box, imitating a quantum system by mimicking the measurement statistics of any viable observable nominated by external observers. Inside a second box lies a genuine quantum system. Either box can be used to…

Quantum Physics · Physics 2015-06-19 Jayne Thompson , Mile Gu , Pawel Kurzynski , Su-Yong Lee , Dagomir Kaszlikowski

Wheeler's delayed choice experiment, a well known manifestation of the complementarity principle, has proved somewhat difficult to physically interpret. We show that, restated in quantum field theoretic language, the experiment submits to a…

Quantum Physics · Physics 2007-05-23 R. Srikanth

Experimental designs are fundamental for estimating causal effects. In some fields, within-subjects designs, which expose participants to both control and treatment at different time periods, are used to address practical and logistical…

Methodology · Statistics 2025-05-08 Justin Ho , Jonathan Min

Delayed choice and quantum eraser experiments have attracted much interest recently, both theoretically and experimentally. In particular, they have prompted suggestions that quantum mechanics involves acausal effects. Using a recently…

Quantum Physics · Physics 2008-10-22 George Jaroszkiewicz

Surrogate modeling of costly mathematical models representing physical systems is challenging since it is typically not possible to create a large experimental design. Thus, it is beneficial to constrain the approximation to adhere to the…

Machine Learning · Computer Science 2023-09-06 Lukáš Novák , Himanshu Sharma , Michael D. Shields

We study causal discovery from observational data in linear Gaussian systems affected by \emph{mixed latent confounding}, where some unobserved factors act broadly across many variables while others influence only small subsets. This…

Machine Learning · Computer Science 2026-01-01 Amir Asiaee , Samhita Pal , James O'quinn , James P. Long

Causal structure learning is a key problem in many domains. Causal structures can be learnt by performing experiments on the system of interest. We address the largely unexplored problem of designing a batch of experiments that each…

Machine Learning · Computer Science 2021-11-25 Scott Sussex , Andreas Krause , Caroline Uhler

In this article, we present a detailed analysis of two famous delayed choice experiments: Wheeler's classic gedanken-experiment and the delayed quantum eraser. Our analysis shows that the outcomes of both experiments can be fully explained…

Quantum Physics · Physics 2024-02-13 Marijn Waaijer , Jan van Neerven

The problem of fair classification can be mollified if we develop a method to remove the embedded sensitive information from the classification features. This line of separating the sensitive information is developed through the causal…

Machine Learning · Computer Science 2020-12-10 Hyemi Kim , Seungjae Shin , JoonHo Jang , Kyungwoo Song , Weonyoung Joo , Wanmo Kang , Il-Chul Moon

Environment induced decoherence, and other quantum processes, have been proposed in the literature to explain the apparent spontaneous selection - out of the many mathematically eligible bases - of a privileged measurement basis that…

General Physics · Physics 2016-09-27 Hitoshi Inamori

A central question for causal inference is to decide whether a set of correlations fit a given causal structure. In general, this decision problem is computationally infeasible and hence several approaches have emerged that look for…

Quantum Physics · Physics 2018-07-26 Mirjam Weilenmann , Roger Colbeck

Identifying latent representations or causal structures is important for good generalization and downstream task performance. However, both fields have been developed rather independently. We observe that several methods in both…

Machine Learning · Statistics 2025-02-11 Patrik Reizinger , Siyuan Guo , Ferenc Huszár , Bernhard Schölkopf , Wieland Brendel

The delayed choice experiments are a collection of experiments where the counterintuitive laws of quantum mechanics are manifested in a very striking way. Although the delayed choice experiments can be very accurately described with the…

Quantum Physics · Physics 2010-07-23 Bram Gaasbeek

Quantum entanglement is known as a unique quantum feature that cannot be obtained by classical physics. Over the last several decades, however, such an understanding on quantum entanglement might have confined us in a limited world of weird…

Quantum Physics · Physics 2023-08-01 B. S. Ham

Controlled Direct Effect (CDE) is one of the causal estimands used to evaluate both exposure and mediation effects on an outcome. When there are unmeasured confounders existing between the mediator and the outcome, the ordinary…

Methodology · Statistics 2024-10-30 Shunichiro Orihara , Shinpei Imori , Kosuke Morikawa , Atsushi Goto , Masataka Taguri

It is well known that Wheeler proposed several delayed choice experiments in order to show the impossibility to speak of the way a quantum system behaves before being detected. In a double-slit experiment, when do photons decide to travel…

Quantum Physics · Physics 2017-10-11 Hervé Zwirn

Causal knowledge is vital for effective reasoning in science, as causal relations, unlike correlations, allow one to reason about the outcomes of interventions. Algorithms that can discover causal relations from observational data are based…

Machine Learning · Statistics 2019-11-12 Anish Dhir , Ciarán M. Lee

Causal inference is known to be very challenging when only observational data are available. Randomized experiments are often costly and impractical and in instrumental variable regression the number of instruments has to exceed the number…

Methodology · Statistics 2018-06-19 Dominik Rothenhäusler , Peter Bühlmann , Nicolai Meinshausen