Quantum operations with indefinite causal order (ICO) represent a framework in quantum information processing where the relative order between two events can be indefinite. In this paper, we investigate whether sensing and computation, two canonical tasks in quantum information processing, can be carried out within the ICO framework. We propose a scheme for integrated sensing and computation that uses the same quantum state for both tasks. The quantum state is represented as an agent that performs state observation and learns a function of the state to make predictions via a parametric model. Under an ICO operation, the agent experiences a superposition of orders, one in which it performs state observation and then executes the required computation steps, and another in which the agent carries out the computation first and then performs state observation. This is distinct from prevailing information processing and machine intelligence paradigms where information acquisition and learning follow a strict causal order, with the former always preceding the latter. We provide experimental results and we show that the proposed scheme can achieve small training and testing losses on a representative task in magnetic navigation.
Quantum operations with indefinite causal order (ICO) represent a framework in quantum information processing where the relative order between two events can be indefinite. In this paper, we investigate whether sensing and computation, two canonical tasks in quantum information processing, can be carried out within the ICO framework. We propose a scheme for integrated sensing and computation that uses the same quantum state for both tasks. The quantum state is represented as an agent that performs state observation and learns a function of the state to make predictions via a parametric model. Under an ICO operation, the agent experiences a superposition of orders, one in which it performs state observation and then executes the required computation steps, and another in which the agent carries out the computation first and then performs state observation. This is distinct from prevailing information processing and machine intelligence paradigms where information acquisition and learning follow a strict causal order, with the former always preceding the latter. We provide experimental results and we show that the proposed scheme can achieve small training and testing losses on a representative task in magnetic navigation.
In the classical world, physical events always happen in a fixed causal order.However, it was recently revealed that quantum mechanics allows events to occur with indefinite causal order (ICO).In this study, we use an optical quantum switch to experimentally investigate the application of ICO in thermodynamic tasks.Specifically, we simulate the working system interacting with two identical thermal reservoirs in an ICO, observing the quantum heat extraction even though they are in thermal equilibrium where heat extraction is inaccessible by traditional thermal contact.Using such a process, we simulate an ICO refrigeration cycle and investigate its properties.We also show that by passing through the ICO channel multiple times, one can extract more heat per cycle and thus obtain a higher refrigeration performance.Our results suggest that the causal nonseparability can be a powerful resource for quantum thermodynamic tasks.
In classical physics, events follow a definite causal order: the past influences the future, but not the reverse. Quantum theory, however, permits superpositions of causal orders—the so-called indefinite causal orders (ICOs)—which can provide operational advantages over classical scenarios. Verifying such phenomena has sparked significant interest, much like earlier efforts devoted to refuting local realism and confirming quantum entanglement. To date, demonstrations of ICO have all been based a process called the quantum switch and have relied on device-dependent or semi-device-independent protocols. Achieving a device-independent verification of ICO would imply that nature allows for correlations that do not respect causality, independent of any experimental assumptions or underlying theoretical description of the experiment. To this end, a recent theoretical development introduced a Bell-like inequality that allows for fully device-independent verification of ICO in a quantum switch. Here we implement this verification by experimentally violating this inequality. In particular, we measure a value of 1.8328 ± 0.0045 , which is 18 standard deviations above the definite causal order bound of 1.75 . Our work presents the first implementation of a device-independent protocol to verify ICO, albeit in the presence of experimental loopholes. This represents an important step toward the device-independent verification of an ICO and provides a context in which to identify loopholes specifically related to the verification of ICO.
Indefinite causal order (ICO), in which the order of quantum operations is placed in a coherent superposition, has been demonstrated to enhance various information-processing tasks. Here, we investigate its impact on the thermodynamic processes generated by thermalizing quantum channels. We consider a two-level system interacting with two thermal baths under a quantum SWITCH, with the channel order controlled coherently by an ancillary qubit. We derive closed-form expressions for the effective inverse temperature βf of the postselected system state for both identical and distinct bath temperatures, and identify the control-qubit parameters that maximize heating or cooling. Our analysis reveals how the diagonal and coherent components of the control-qubit state contribute separately to the temperature shift, and how their interplay enables departures from the thermal response attainable under protocols with a definite causal order within the thermodynamic setting considered here. Bath asymmetry enhances these effects, while reduced purity of the control qubit state suppresses them. These results provide a systematic framework for assessing SWITCH-based thermalization in the setting of indefinite causal order, and identify control-qubit coherence as a tunable resource.
This work reports experimental evidence of indefinite causal order in a quantum process characterized by a 6×6 process matrix. The model was constructed step-by-step from an empirical basis of four distinct types of quantum experiments (Bell tests, Leggett-Garg inequalities, weak measurements, and delayed-choice experiments), naturally leading to an atypical quantum model that defies conventional interpretations. The emergent structure occupies an intermediate (Madhyamika) position between realism and QBism, exhibiting features that challenge both local and non-local descriptions in spatial and temporal domains. The model's characteristics align most closely with Carlo Rovelli's Relational Interpretation, where quantum properties are not absolute but exist in relation to specific physical interactions. Has similarities with TSVF and Costa de Beauregard's models, but also some significative differences. Using methods of causal projection and witness optimization, the study identifies signatures of causal indefiniteness, quantified by a causal error of 0.1488±0.0001. The process exhibits a 75% ICO score indicating moderate evidence of indefinite causal order, with CHSH value 2.753 achieving 90.95% of the standard quantum bound. The analysis includes comprehensive statistical validation via bootstrap methods and comparison with synthetic causal and non-causal processes. The causal incompatibility persists under bootstrap resampling with injected noise up to σ=0.01, demonstrating robustness of the effect. The experimental process shows 3.2× greater causal error than reference ICO benchmarks. So the model would be falsifiable through various types of experiments not difficult to design. Key quantum characteristics include entanglement negativity of 0.474 and total coherence of 0.315, supporting genuine quantum signatures beyond classical causal models. The complete Python code for the analysis, including process matrix optimization, causal projection, witness optimization, and statistical validation, is provided. The work not only contributes to understanding fundamental limits of quantum causality but also provides an empirically grounded framework that bridges multiple quantum phenomena within a unified relational context, potentially facilitating new approaches to quantum information processing beyond conventional causal structures.
Indefinite causal order (ICO), a striking feature of quantum mechanics, has attracted broad theoretical and experimental interest. While ICO holds promise for quantum information processing, akin to quantum entanglement, its experimental realization and rigorous verification remain fundamental challenges. Here, we demonstrate and certify generalized multidimensional multipartite ICOs using a programmable integrated-photonic quantum chip implementing a generalized quantum switch. By violating definite causal order bounds with high statistical significance, we experimentally characterize and verify these generalized ICOs. Furthermore, we explore a resource theory of causal nonseparability by implementing a single-copy distillation protocol. Our Letter constitutes a major step toward a generalized framework for quantum causality.
Quantum resources can, in principle, enable Heisenberg-limited (HL) sensing, yet no-go theorems imply that HL scaling is generically unattainable in realistic noisy devices. While quantum error correction (QEC) can suppress noise, its use in quantum sensing is constrained by stringent requirements, including prior noise characterization, restrictive signal-noise compatibility conditions, and measurement-based syndrome extraction with global control. Here we introduce an ICO-based QEC protocol, providing the first application of indefinite causal order (ICO) to QEC. By coherently placing auxiliary controls and noisy evolution in an indefinite causal order, the resulting noncommutative interference enables an auxiliary system to herald and correct errors in real time, thereby circumventing the limitations of conventional QEC and restoring HL scaling. We rigorously establish the protocol for single- and multi-noise scenarios and demonstrate its performance in single-qubit, many-body, and continuous-variable platforms. We further identify regimes in which error correction can be implemented entirely by unitary control, without measurements. Our results reveal ICO as a powerful resource for metrological QEC and provide a broadly applicable framework for noise-resilient quantum information processing.