Abstract We present a new verification scheme for universal quantum computers that yields the number of working qubits and measures the noise expected when executing quantum circuits. It is based on detecting the standard deviation of the meta-probability distribution of output values for a single qubit probed by random quantum gates involving all the qubits of the quantum computer. This result is generated directly from the output statistics of the quantum computer and thus does not require any assistance from classical computers. With current technology quantum computers with up to 40 qubits could be tested employing this method, but in future, given faster quantum processors, it might be used to demonstrate quantum supremacy. Our results have been successfully demonstrated on a real quantum computer (IBM-Cairo).
Abstract We present a new verification scheme for universal quantum computers that yields the number of working qubits and measures the noise expected when executing quantum circuits. It is based on detecting the standard deviation of the meta-probability distribution of output values for a single qubit probed by random quantum gates involving all the qubits of the quantum computer. This result is generated directly from the output statistics of the quantum computer and thus does not require any assistance from classical computers. With current technology quantum computers with up to 40 qubits could be tested employing this method, but in future, given faster quantum processors, it might be used to demonstrate quantum supremacy. Our results have been successfully demonstrated on a real quantum computer (IBM-Cairo).
While quantum speed-up in solving certain decision problems by a fault-tolerant universal quantum computer has been promised, a timely research interest includes how far one can reduce the resource requirement to demonstrate a provable advantage in quantum devices without demanding quantum error correction, which is crucial for prolonging the coherence time of qubits. We propose a model device made of locally interacting multiple qubits, designed such that simultaneous single-qubit measurements on it can output probability distributions whose average-case sampling is classically intractable, under similar assumptions as the sampling of noninteracting bosons and instantaneous quantum circuits. Notably, in contrast to these previous unitary-based realizations, our measurement-based implementation has two distinctive features. (i) Our implementation involves no adaptation of measurement bases, leading output probability distributions to be generated in constant time, independent of the system size. Thus, it could be implemented in principle without quantum error correction. (ii) Verifying the classical intractability of our sampling is done by changing the Pauli measurement bases only at certain output qubits. Our usage of random commuting quantum circuits in place of computationally universal circuits allows a unique unification of sampling and verification, so they require the same physical resource requirements in contrast to the more demanding verification protocols seen elsewhere in the literature.
We introduce a distributed classical simulation algorithm for general quantum circuits, and present numerical results for calculating the output probabilities of universal random circuits. We find that we can simulate more qubits to greater depth than previously reported using the cluster supported by the Data Infrastructure and Search Technology Division of the Alibaba Group. For example, computing a single amplitude of an 8×8 qubit circuit with depth 40 was previously beyond the reach of supercomputers. Our algorithm can compute this within 2 minutes using a small portion (≈ 14% of the nodes) of the cluster. Furthermore, by successfully simulating quantum supremacy circuits of size 9×9×40, $10\times 10\times 35 $, 11×11×31, and $12\times 12\times 27 $, we give evidence that noisy random circuits with realistic physical parameters may be simulated classically. This suggests that either harder circuits or error-correction may be vital for achieving quantum supremacy from random circuit sampling.
Recent devices, using hundreds of superconducting quantum bits, claim to perform quantum computing. However, it is not an easy task to determine and quantify the degree of quantum coherence and control used by these devices. Namely, it is a difficult task to know with certainty whether or not a given device (e.g., the D-Wave One or D-Wave Two) is a quantum computer. Such a verification of quantum computing would be more accessible if we already had some kind of working quantum computer, to be able to compare the outputs of these various computing devices. Moreover, the verification process itself could strongly depend on whether the tested device is a standard (gate-based) or, e.g., an adiabatic quantum computer. Here we do not propose a technical solution to this quantum-computing “verification problem”, but rather outline the problem in a way which would help both specialists and non-experts to see the scale of this difficult task, and indicate some possible paths towards its solution.
We present EHands, a quantum-native protocol for implementing multivariable polynomial transformations on quantum processors. The protocol introduces four fundamental, reversible operators: multiplication, addition, negation, and parity flip, and employs the Expectation Value ENcoding (EVEN) scheme to represent real numbers as quantum states. Unlike discretization or binary encoding methods, EHands operates directly on vectorized real-valued inputs prepared in the initial state and applies a shallow quantum circuit that depends only on the polynomial coefficients. The result is obtained from the expectation value measured on a single qubit, enabling efficient parallel evaluation of a polynomial across multiple data points using a single circuit. We introduce both a reversible implementation for degree-d polynomials, requiring 3d qubits, and a non-reversible variant that uses qubit resets to reduce the requirements to d+1 qubits. Both implementations exhibit linear depth scaling in d and are explicitly decomposed into one- and two-qubit gates for direct execution on current quantum processing units. The protocol's effectiveness is demonstrated through experimental validation on IBM's Heron-class quantum processors, showing reliable polynomial approximations of functions like ReLU and arctan.
We present verification protocols to gain confidence in the correct performance of the realization of an arbitrary universal quantum computation. The derivation of the protocols is based on the fact that matchgate computations, which are classically efficiently simulable, become universal if supplemented with additional resources. We combine tools from weak simulation, randomized compiling, and classical statistics to derive verification circuits. These circuits have the property that (i) they strongly resemble the original circuit and (ii) cannot only be classically efficiently simulated in the ideal, i.e. error free, scenario, but also in the realistic situation where errors are present. In fact, in one of the protocols we apply exactly the same circuit as in the original computation, however, to a slightly modified input state.
Randomized algorithms are crucial subroutines in quantum computing, but the requirement to execute many types of circuits on a real quantum device has been challenging to their extensive implementation. In this study, we propose an engineering method to reduce the executing time for randomized algorithms using dynamic circuits, i.e., quantum circuits involving intermediate measurement and feedback processes. The main idea is to generate the probability distribution defining a target randomized algorithm on a quantum computer, instead of a classical computer, which enables us to implement a variety of static circuits on a single dynamic circuit with many measurements. We applied the proposed method to the task of random Pauli measurement for one qubit on an IBM superconducting device, showing that a 14,000-fold acceleration of executing time was observed compared with a conventional method using static circuits. Additionally, for the problem of estimating expectation values of 28- and 40-qubit hydrogen chain models, we successfully applied the proposed method to realize the classical shadow with 10 million random circuits, which is the largest demonstration of classical shadow. This work significantly simplifies the execution of randomized algorithms on real quantum hardware.