We present two complementary viewpoints for combining quantum computers and the foundations of quantum mechanics.On the one hand, ideal devices can be used as test beds for experimental tests of the foundations of quantum mechanics: We provide algorithms for the Peres test for complex numbers in quantum superpositions and the Sorkin test of Born's rule.On the other hand, noisy intermediate-scale quantum devices can be benchmarked using these same tests.These are deep quantum benchmarks based on the foundations of quantum theory itself.We present test data from Rigetti hardware.
We present two complementary viewpoints for combining quantum computers and the foundations of quantum mechanics.On the one hand, ideal devices can be used as test beds for experimental tests of the foundations of quantum mechanics: We provide algorithms for the Peres test for complex numbers in quantum superpositions and the Sorkin test of Born's rule.On the other hand, noisy intermediate-scale quantum devices can be benchmarked using these same tests.These are deep quantum benchmarks based on the foundations of quantum theory itself.We present test data from Rigetti hardware.
We present two complementary viewpoints for combining quantum computers and the foundations of quantum mechanics. On one hand, ideal devices can be used as testbeds for experimental tests of the foundations of quantum mechanics: we provide algorithms for the Peres test of the superposition principle and the Sorkin test of Born's rule. On the other hand, noisy intermediate-scale quantum (NISQ) devices can be benchmarked using these same tests. These are deep-quantum benchmarks based on the foundations of quantum theory itself. We present test data from Rigetti hardware.
We use quantum computers to test the foundations of quantum mechanics through quantum algorithms that implement some of the experimental tests as the basis of the theory's postulates. These algorithms can be used as a test of the physical theory under the premise of a perfect hardware or as a test of the hardware under the premise that quantum theory is correct. In this paper, we show how the algorithms can be used to test the efficacy of a quantum computer in obeying the postulates of quantum mechanics. We study the effect of different types of errors on the results of experimental tests of the postulates. A salient feature of this error analysis is that it is deeply rooted in the fundamentals of quantum mechanics as it highlights how systematic errors affect the quantumness of the quantum computer.
We outline a proposal to test quantum mechanics in the high-complexity regime using noisy intermediate-scale quantum (NISQ) devices. The procedure involves simulating a non-Clifford random circuit, followed by its inverse, and then checking that the resulting state is the same as the initial state. We are motivated by the hypothesis that quantum mechanics is not fundamental, but instead emerges from a theory with less computational power, such as classical mechanics. This emergent quantum mechanics (EmQM) hypothesis makes the prediction that quantum computers will not be capable of sufficiently complex quantum computations. We show that quantum mechanics predicts that the fidelity of our procedure decays exponentially with circuit depth (due to noise in NISQ devices), while EmQM predicts that the fidelity will decay significantly more rapidly for sufficiently deep circuits, which is the experimental signature that we propose to search for. We estimate rough bounds for when possible signals of EmQM should be expected. Furthermore, we find that highly informative experiments should require only thousands qubits.
In the near-term "NISQ"-era of noisy, intermediate-scale, quantum hardware and beyond, reliably determining the quality of quantum devices becomes increasingly important: users need to be able to compare them with one another, and make an estimate whether they are capable of performing a given task ahead of time. In this work, we develop and release an advanced quantum benchmarking framework in order to help assess the state of the art of current quantum devices. Our testing framework measures the performance of universal quantum devices in a hardware-agnostic way, with metrics that are aimed to facilitate an intuitive understanding of which device is likely to outperform others on a given task. This is achieved through six structured tests that allow for an immediate, visual assessment of how devices compare. Each test is designed with scalability in mind, making this framework not only suitable for testing the performance of present-day quantum devices, but also of those released in the foreseeable future. The series of tests are motivated by real-life scenarios, and therefore emphasise the interplay between various relevant characteristics of quantum devices, such as qubit count, connectivity, and gate and measurement fidelity. We present the benchmark results of twenty-one different quantum devices from IBM, Rigetti and IonQ.
Quantum computing represents a transformative shift in computational technology, leveraging the principles of quantum mechanics to process information in ways that surpass the limits of classical systems.By exploiting qubits, superposition, entanglement, and quantum parallelism, quantum computers offer the potential to solve certain classes of problems-such as optimization, cryptography, molecular simulation, and complex machine learning tasks-significantly faster than classical algorithms.With rapid advancements in quantum hardware and the emergence of Noisy Intermediate-Scale Quantum (NISQ) devices, quantum computing has evolved from a theoretical concept to a practical field with growing industrial and scientific relevance.Although current systems face challenges related to error rates, decoherence, and scalability, ongoing developments in quantum error correction, hybrid quantum-classical algorithms, and software frameworks like Qiskit, Cirq, and PennyLane continue to push the field forward.This paper provides an introductory overview of quantum computing, outlining its foundational principles, current technological landscape, key algorithms, and future research directions.The goal is to offer a clear understanding of how quantum computing is poised to reshape the future of computation.
The transition from theoretical quantum mechanics to practical quantum computing represents one of the most significant technological developments of the 21st century. This comprehensive survey examines the evolution from foundational quantum mechanical principles to contemporary quantum computing implementations. We analyze how fundamental quantum phenomena—superposition, entanglement, and unitary evolution—are systematically harnessed to achieve computational advantages over classical systems. The paper provides detailed analysis of key quantum algorithms including Deutsch-Jozsa, Grover's search, and Shor's factorization algorithm, emphasizing their theoretical foundations and computational complexity advantages. We present a comparative evaluation of current hardware platforms including superconducting qubits, trapped ions, photonic systems, and semiconductor quantum dots, analyzing their respective merits, limitations, and scalability prospects. The challenges of quantum error correction, decoherence mitigation, and the path toward fault-tolerant quantum computation are critically examined within the context of the current Noisy Intermediate-Scale Quantum (NISQ) era. This interdisciplinary synthesis bridges theoretical quantum mechanics and practical quantum computing, highlighting the remarkable progress achieved and the substantial challenges that remain in realizing the full potential of quantum computation.