Higher-dimensional symmetric informationally complete measurement via programmable photonic integrated optics
Abstract
Symmetric informationally complete measurements are both important building blocks in many quantum information protocols and the seminal example of a generalised, non-orthogonal, quantum measurement. In higher-dimensional systems, these measurements become both increasingly interesting and increasingly complex to implement. Here, we demonstrate an integrated quantum photonic platform to realize such a measurement on three-level quantum systems. The device operates at the high fidelities necessary for verifying a genuine many-outcome quantum measurement, performing near-optimal quantum state discrimination, and beating the projective limit in quantum random number generation. Moreover, it is programmable and can readily implement other quantum measurements at similarly high quality. Our work paves the way for the implementation of sophisticated higher-dimensional quantum measurements that go beyond the traditional orthogonal projections.
I Introduction
Standard measurements in quantum theory are projections onto a basis in -dimensional Hilbert space. However, in the modern form of quantum theory, there exist more complex measurements, that can on their own be tomographically complete, with up to outcomes, while remaining irreducible D’Ariano et al. (2005). That is, they cannot be simulated by stochastically combining any other quantum measurements. The most prominent example of such generalised quantum measurements is a symmetric informationally complete (SIC) measurement Renes et al. (2004). Its defining property, in addition to tomographic completeness and irreducibility, is outcomes being fully symmetric in Hilbert space.
Much research has been devoted to theoretically constructing these measurements Fuchs et al. (2017). While they find many applications in quantum information, they are also connected to some interpretations of quantum theory Fuchs and Schack (2013) and well-known mathematics problems Appleby et al. (2017). In quantum information, SIC measurements are natural for many important tasks. Examples are state tomography Scott (2006); Stricker et al. (2022), entanglement detection Shang et al. (2018); Morelli et al. (2023) and random number generation Acín et al. (2016); Tavakoli et al. (2021). They are also relevant for quantum certification protocols Tavakoli et al. (2019), quantum key distribution Renes (2005); Tavakoli et al. (2020) and tests of nonlocality and contextuality Bengtsson et al. (2012); Tavakoli et al. (2021). Naturally, there has been considerable interest in experimentally realising SIC measurements. However, the implementation of generalised measurements comes with additional challenges. It requires control of ancillary quantum systems and entangling gate operations. In the case of SIC measurements, the challenge is particularly pronounced, as one must simultaneously resolve the maximal number of outcomes while also achieving uniform Hilbert space angles by control of populations and phases. Early photonics realisations of SIC measurements are based on simulating it by separately performing several standard measurements and post-selecting on successful outcomes Medendorp et al. (2011); Pimenta et al. (2013); Bent et al. (2015). Faithful implementations, using multiple photonic degrees of freedom for system and ancilla, have been achieved for the simplest, qubit, systems, see e.g. Bian et al. (2015); Zhao et al. (2015); Hou et al. (2018). However, it is well-known that already the interferometry required for realising SIC measurements beyond qubit dimensions is much more demanding Tabia (2012a).
Going beyond binary quantum systems is an important frontier in quantum information science. Higher-dimensional systems propel advantages in many communication protocols. In quantum key distribution, higher-dimensional systems can give better key rates and offer important improvements to the tolerance of noise and loss Hu et al. (2021); Bulla et al. (2023). Similar high-dimensional advantages are encountered in basic quantum information primitives such as entanglement distribution Ecker et al. (2019); Hu et al. (2020). In nonlocality experiments, high-dimensional systems can lead to larger Bell inequality and steering inequality violations Dada et al. (2011); Srivastav et al. (2022). Also in quantum computation, processors have been designed for higher dimensions Paesani et al. (2021); Chi et al. (2022).

It is a natural endeavor to develop measurement devices for beyond-binary quantum systems, that can faithfully implement not only standard but also generalised quantum measurements. Notably, a higher-dimensional generalised measurement has been reported Martínez et al. (2023), but it is conceptually different from a SIC measurement because it is neither tomographically complete nor motivated by established quantum information tasks. The biggest challenge in high dimensional SIC measurements is that the complexity of constructing measurements increases rapidly with increasing dimensions. A promising avenue to overcome this challenge is photonic integrated circuits (PICs), which provide high stability and scalability and are developing into a promising platform for quantum photonic experiments Wang et al. (2020); Feng et al. (2022a). Many quantum applications including logic gates Crespi et al. (2011); Feng et al. (2022b), higher-dimensional entanglement with standard measurements Wang et al. (2018); Lu et al. (2020); Chi et al. (2022), tests of Boson Sampling Crespi et al. (2013); Arrazola et al. (2021), quantum teleportation Llewellyn et al. (2020) and frustrated quantum interference Feng et al. (2023) have been demonstrated with PICs. Photonic quantum states can be directly generated, manipulated, and detected on integrated chips. Moreover, because of the high interferometric visibility and phase stability, quantum PIC with many passive and active components is particularly attractive to construct large-scale programmable quantum photonic processors. To date, quantum PICs have been expanded to contain thousands of components Bao et al. (2023) and dozens of photons Arrazola et al. (2021).
Here, we develop a PIC device that can faithfully implement generalised quantum measurements, in the form of SIC measurements on three-level quantum systems. Our device operates at high quality, clearly achieving the standards necessary both for demonstrating physical properties well beyond those of standard, projective, measurements, and for harvesting the advantages of generalised measurements in quantum information protocols. Specifically, this is demonstrated through detector tomography, through a range of verification and simulation tasks and through quantum random number generation. In addition, the device is versatile as it can be readily programmed to implement many other measurements. We demonstrate this feature by realising highly symmetric projections as well as the seminal mutually unbiased bases, and apply them in relevant information tasks.
II Scheme for symmetric informationally complete measurement
A quantum measurement in dimension with outcomes is described by a collection of positive semi-definite matrices such that . For irreducible standard measurements, are orthogonal projectors and the number of outcomes is at most . For irreducible generalised measurements, one can reach outcomes. The SIC measurement corresponds to choosing where all distinct pairs of modulus overlaps are identical, namely for every . A standard instance of a qutrit SIC measurement corresponds to the following nine (unnormalized) vectors :
(1) |
where .
Generalized measurements can always be achieved through standard projection measurements combined with auxiliary systems which can be achieved through a so-called Naimark dilation Peres (1990). When and the measurement operators, , are proportional to rank-one projectors onto a vector , the matrix must be extended to a larger Hilbert space, in which its columns become orthogonal. Hence, we require an matrix such that is unitary.
We consider the Naimark extension for the SIC measurement corresponding to the following unitary matrix,
(2) |
Here, the rows 1, 4, and 7 correspond to the matrix containing the qutrit SIC states (1). This matrix is to be applied to an incoming qutrit and initialised ancilla qutrit (), with the former ordered on ports . In order to reduce the complexity of implementing the unitary transformation , we decompose the matrix into a sequence of three-dimensional subspace operations. These are shown in Fig. 1a, in terms of unitaries and (see Supplementary Material), which are unit operations in suitable three-dimensional subspaces Tabia (2012b).
Number of outcomes | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
---|---|---|---|---|---|---|---|---|
for SIC measurement | 0.4330 | 0.7931 | 0.8898 | 0.9269 | 0.9571 | 0.9714 | 0.9874 | 1 |
for tomographic reconstruction | 0.4549 | 0.8332 | 0.9320 | 0.9690 | 0.9918 | 1 | 1 | 1 |
Maximal for exact preparations | 0.2073 | 0.2874 | 0.3088 | 0.3171 | 0.3238 | 0.3270 | 0.3305 | |
Maximal for imprecise preparation | 0.2169 | 0.3082 | 0.3231 | 0.3277 | 0.3313 | 0.3325 | 0.3333 |
III Implementation
We use a reconfigurable silicon photonic integrated circuit to implement the high-dimensional SIC measurement scheme. Silicon photonics show sizable advantages in scaling and functionality with low-cost, CMOS-compatible fabrication and ultra-high integration density Thomson et al. (2016). As shown in Fig. 1b, the device we developed consists of a cascade of Mach-Zehnder interferometers (MZIs) and multiple phase shifters, which are programmed to realize the expected operations given below. The total chip size is just 3.31.0, and all phase shifters are characterized with average interference visibility over 0.99.
Depending on the function, the device is divided into two parts, the state preparation part (region I) and the measurement part (regions II, III, IV). In the state preparation part, any three-dimensional pure state can be constructed using two MZIs and phase shifters. The subsequent measurement apparatus, with three inputs and nine outputs, can be switched between several different settings. For example, by adjusting the phase shifter, one can switch from a nine-outcome SIC measurement to different sets of mutually unbiased basis measurements. In the case of SIC measurement, in our scheme, we only need to implement the unitary operation on three-dimensional subspaces. As shown in Fig 1, we sequentially perform the unitaries , , and operations on the three-dimensional subspaces in the II, III, and IV regions, ultimately resulting in 9 outputs. In contrast, mutually unbiased bases, being standard projective measurements, require only a unitary operation of 3 inputs and 3 outputs. They can be implemented by resetting the phase of the phase shifter. The specific phase shifter settings and further details on the PIC device can be found in the supplementary materials.
In the experiment, a CW laser at 775 nm is used to pump a type II PPKTP crystal to generate correlated photon pairs Feng et al. (2022b). They are coupled into different singe-mode fibers, and one photon is detected directly to herald the existence of another. The photons show a coherence time of about 1.5 ps. The heralded single photons are coupled into the silicon quantum photonic processor through the single-mode fiber and on-chip grating coupler, and the qutrit states are generated and analyzed on the single chip.
IV Tomography and verification of the SIC measurement.
A central question is to gauge how accurately the measurement implemented on our device corresponds to the SIC measurement. For this purpose, we discuss several different verification methods. Details are given in Supplementary Material.
Tomography
The most immediate approach is to perform detector tomography for the device. To this end, we have prepared the tomographically complete set of qutrit states given in Eq. (1). Probabilities were inferred from the relative frequencies in the nine different ports of the device. The tomographic reconstruction of the measurement operators was based on a standard maximum likelihood method Fiurášek (2001). The estimated fidelity of each of the operations corresponding to the nine possible outcomes are , , , , , , , and respectively. The average fidelity is .

IV.1 Simulation of tomographic reconstruction
To benchmark the quality of our lab measurement, we investigate whether it can be simulated by stochastically combining quantum measurements with at most outcomes. If no -outcome simulation exists, we conclude that must genuinely necessitate at least outcomes. Notably, defying a simulation with implies a truly generalised, non-projective, measurement.
For each , we either construct an explicit simulation or quantify its failure through the minimal rate of noise that must be added to the measurement to make the simulation possible. To this end, we take the artificially mix the lab measurement with noise of uniform spectral density, , for some visibility parameter . Here, the lab measurement is represented by the tomographic reconstruction. Now, we seek the largest visibility, , for which admits an -outcome simulation. Notably, any value implies that cannot be simulated. Using semidefinite programming Tavakoli et al. (2023), following the technique of Ref. Oszmaniec et al. (2017), we can compute . The results are displayed in Table 1. The lab measurement clearly defies the projective limit since , instead requiring outcomes for a simulation.
However, this procedure has a significant drawback that may lead to an underestimation of the quality of the lab measurement. The tomographic reconstruction depends significantly on both the specific data analysis method and it is vulnerable to tiny experimental deviations in the state preparation Rosset et al. (2012). These effects are especially relevant in our case, due to the small gap between the noise rates for large in the first row of Table 1. Next, we set out to eliminate these issues.
IV.2 Simulation of quantum state discrimination
We now use the basic quantum information primitive of state discrimination to benchmark our implementation of the SIC measurement. Consider that we draw, with uniform probability, one of the nine states in Eq. (1) and try to recover the classical label via a measurement. The success probability of state discrimination is . In particular, the best measurement, namely the SIC measurement, would achieve . We have used semidefinite programs to compute the largest value of achievable with arbitrary quantum measurements with at most outcomes. The results are shown in the third row of Tab 1. In particular, projective measurements satisfy the tight inequality .
The probability distributions in our implementation of the state discrimination are shown in Fig 2. The results closely agree with the theoretical prediction for the SIC measurement. We observe from a total of roughly counts. This is far above the projective measurement limit and, notably, even somewhat about the limit for the SIC measurement. However, the latter is statistically insignificant. Putting the experimental value even five standard deviations below the mean still exceeds the eight-outcome measurement limit . The -value, obtained from the Hoeffding inequality Hoeffding (1963), for the mean violation of the eight-outcome limit is of order . This implies a genuine nine-outcome measurement, which is a substantial improvement on the tomography-based approach. Indeed, the tomographic reconstruction would predict a far smaller value () than observed in the lab.
The verification of the measurement can be further strengthened by eliminating the assumption that the nine preparations are exactly controlled. Following the ideas of Tavakoli (2021), we permit any qutrit state with limited infidelity to the target preparation. Our average measured preparation infidelity is . In the final row of Tab 1, we have estimated the resulting correction of for -outcome measurements. While if the preparation device optimally leverages the allowed infidelity, it becomes impossible to beat the eight-outcome limit, our reported mean still exceeds the seven-outcome limit.
V Protocols
We consider the use of the measurement device for protocols beyond the purpose of benchmarking the device. In our three case studies, we showcase also the programmability of the measurement device. Details on the protocols and our experiments are found in Supplementary Material.
V.1 Quantum random numbers

Having no more than outcomes, irreducible projective measurements cannot generate more than bits of randomness. In contrast, generalised measurements can break this limit. The SIC measurement is ideal for the purpose as it features a maximal number of outcomes and is fully unbiased. In our analysis, we treat the device as a black box and assume that we can probe it with known qutrit states; a so-called measurement-device-independent scenario. Our protocol is based on quantum state exclusion: we probe the SIC measurement with preparations . Thus, each is mixed and orthogonal to the SIC state . The prediction is then a distribution , which is zero if and uniform otherwise. It has bits of randomness for any choice of .
The probabilities estimated in our implementation are displayed in Fig. 3. They correspond accurately to the prediction. The randomness of our data can be evaluated using the methods of Šupić et al. (2017) but the evaluation ultimately depends on how relative frequencies are chosen to correspond to probabilities. While this can make the final randomness vary to a small extent, it is consistently well above the projective limit of bits. For instance, if we permit five (twelve) standard deviations in fluctuations about the relative frequency for (), we obtain bits. Roughly the same is found when permitting fluctuations corresponding to ten percent of each relative frequency. A small increase is found when the randomness is calculated from the tomographic reconstruction, where fluctuations are not taken into account.
V.2 Beating dense coding protocols with single qutrits
Next, we program our device to perform a complete set of four mutually unbiased basis projections. We use this to produce qutrit correlations that elude the typically stronger resource of qubit communication assisted by qubit entanglement, i.e. protocols à la dense coding Pauwels et al. (2022). We measure each of the nine SIC states (1) in each of the four bases, with the goal of avoiding a forbidden outcome in each setting. This protocol is rather versatile; it has been used for quantum games Emeriau et al. (2022), proofs of contextuality Bengtsson et al. (2012) and entanglement detection schemes Huang et al. (2021). The average probability, , of observing the forbidden event is zero in a perfect implementation but cannot be reduced further than in any dense coding protocol. In our implementation, we collect roughly counts for each of the 36 settings of the experiment. We observe , which clearly demonstrates a qutrit advantage.
V.3 Randomised matching
Finally, we program the device to implement a set of four rank-one projections that together form a maximally distinguishable set of fully symmetric vectors. These are states with the property that is constant and minimal for all . For , they are given by . Such projections have useful e.g. for entanglement detection Morelli et al. (2023); Shi (2023) and uncertainty relations Rastegin (2023). We use them to beat the classical limit in a simple communication problem.
Alice and Bob privately and randomly select four-valued symbols and and attempt to decide whether their selections are identical, but may only communicate a trit message. If identical, Bob must output and if not he must output . The average success probability of correctly answering the random matching question is given by . It can be shown that classical protocols cannot exceed but a qutrit-based protocol, where Bob’s affirmative outcome () corresponds to a projection onto , achieves .
In our implementation, we have achieved , which significantly outperforms the classical limit and nearly reaches the quantum limit. The statistic corresponds to a total of roughly counts.
VI Conclusion
We have reported on a photonic integrated circuit for implementing a three-dimensional symmetric informationally complete measurement. This demonstrates a faithful realisation, beyond qubit systems, of the perhaps most celebrated type of generalised quantum measurement. Importantly, the quality of the implemented measurement is showcased in a variety of tasks, where it significantly exceeds the limitations of standard, projective, measurements. In principle, our work can be extended to generalized measurements of any dimension combined with mature integrated optics. The results showcase the potential of using integrated photonics towards implementing sophisticated quantum measurements while maintaining both the high quality necessary for harvesting their advantages and the scalability necessary to access such operations in truly higher-dimensional systems. The scalability and programmability of integrated optics for high-dimensional generalized measurement can also be combined with existing light source preparation, transmission, and operation technologies to achieve quantum information tasks at high performance standards.
Funding.
This work was supported by the Innovation Program for Quantum Science and Technology (Nos. 2021ZD0301500, 2021ZD0303200, 2021ZD0301200), the National Natural Science Foundation of China (NSFC) (Nos. T2325022, 62275240, 62061160487, 12004373, and 12374338), Key Research and Development Program of Anhui Province (2022b1302007), CAS Project for Young Scientists in Basic Research (Grant No. YSBR-049), USTC Tang Scholarship, Science and Technological Fund of Anhui Province for Outstanding Youth (2008085J02), the Postdoctoral Science Foundation of China (No. 2021T140647) and the Fundamental Research Funds for the Central Universities. A.T. is supported by the Wenner-Gren Foundation and by the Knut and Alice Wallenberg Foundation through the Wallenberg Center for Quantum Technology (WACQT).
Acknowledgment.
This work was partially carried out at the USTC Center for Micro and Nanoscale Research and Fabrication.
Disclosures.
The authors declare no conflicts of interest.
Data availability.
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
Supplemental document.
See Supplement 1 for supporting content.
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