In ensemble (or bulk) quantum computation, measurements of qubits in an individual computer cannot be performed. Instead, only expectation values can be measured. As a result of this limitation on the model of computation, various important algorithms cannot be processed directly on such computers, and must be modified. We provide modifications of various existing protocols, including algorithms for universal fault--tolerant computation, Shor's factorization algorithm (which can be extended to any algorithm computing an NP function), and some search algorithms to enable processing them on ensemble quantum computers.
In ensemble (or bulk) quantum computation, measurements of qubits in an individual computer cannot be performed. Instead, only expectation values can be measured. As a result of this limitation on the model of computation, various important algorithms cannot be processed directly on such computers, and must be modified. We provide modifications of various existing protocols, including algorithms for universal fault--tolerant computation, Shor's factorization algorithm (which can be extended to any algorithm computing an NP function), and some search algorithms to enable processing them on ensemble quantum computers.
In ensemble (or bulk) quantum computation, all computations are performed on an ensemble of computers rather than on a single computer. Measurements of qubits in an individual computer cannot be performed; instead, only expectation values (over the complete ensemble of computers) can be measured. As a result of this limitation on the model of computation, many algorithms cannot be processed directly on such computers, and must be modified, as the common strategy of delaying the measurements usually does not resolve this ensemble-measurement problem. Here we present several new strategies for resolving this problem. Based on these strategies we provide new versions of some of the most important quantum algorithms, versions that are suitable for implementing on ensemble quantum computers, e.g., on liquid NMR quantum computers. These algorithms are Shor's factorization algorithm, Grover's search algorithm (with several marked items), and an algorithm for quantum fault-tolerant computation. The first two algorithms are simply modified using a randomizing and a sorting strategies. For the last algorithm, we develop a classical-quantum hybrid strategy for removing measurements. We use it to present a novel quantum fault-tolerant scheme. More explicitly, we present schemes for fault-tolerant measurement-free implementation of Toffoli and σ(z)(¼) as these operations cannot be implemented "bitwise", and their standard fault-tolerant implementations require measurement.
In ensemble (or bulk) quantum computation, all computations are performed on an ensemble of computers rather than on a single computer. Measurements of qubits in an individual computer cannot be performed; instead, only expectation values (over the complete ensemble of computers) can be measured. As a result of this limitation on the model of computation, many algorithms cannot be processed directly on such computers, and must be modified. We provide modification of the fault tolerant quantum computation protocols to enable processing on ensemble quantum computers.
Quantum algorithms are conventionally formulated for implementation on a single system of qubits amenable to projective measurements. However, in expectation value quantum computation, such as nuclear magnetic resonance realizations, the computer consists of an ensemble of identical qubit-systems amenable only to expectation value measurements. The prevalent strategy in such expectation value implementations of quantum algorithms has been to retain the conventional formulation's unitary operations but modify its initialization and measurement steps appropriately. This naive approach is not optimal for Grover's algorithm and a shortened version for expectation value quantum computers is presented.
<!--HTML-->A universal fault-tolerant quantum computer that can solve efficiently problems such as integer factorization and unstructured database search requires millions of qubits with low error rates and long coherence times. While the experimental advancement towards realizing such devices will potentially take decades of research, noisy intermediate-scale quantum (NISQ) computers already exist. These computers are composed of hundreds of noisy qubits, i.e. qubits that are not error-corrected, and therefore perform imperfect operations in a limited coherence time. In the search for quantum advantage with these devices, algorithms have been proposed for applications in various disciplines spanning physics, machine learning, quantum chemistry and combinatorial optimization. The goal of such algorithms is to leverage the limited available resources to perform classically challenging tasks. In this talk, I provide an overview of NISQ algorithms, their limitations and potential advantages.
Any computation is necessarily a physical process. The current drive towards increasing speed and miniaturization of computers lead modern technology towards the subatomic domain - quantum computing, where strange quantum behavior takes over from familiar classical notions. The quantum computers have the ability to solve problems with varied computational complexities and more importantly hard problems. A problem is said to be hard, if the best possible algorithm requires exponential resources. This exponential quantum parallelism is the basis for the quantum speedup of many algorithms, and has made the construction of fast algorithms for quantum computers possible. Various proposals exist for modeling and devising procedures on computational problems related to factoring, searching, quantum counting, generalization of quantum algorithms etc. (Shor, 1994). In this paper, we have discussed the importance of algorithms such as order-finding, factoring and quantum searching which require exorbitant resources for their solution which otherwise is impossible on a classical computer
By using quantum mechanics to perform calculations classical systems are unable to handle, quantum computing has become a groundbreaking field. Progress in quantum algorithms, quantum simulations, and reliable architectures is reviewed in this paper. Recent research on the Hidden Subgroup Problem reveals links to lattice-based cryptography. Important algorithms such as Shor's for factoring and Grover's for searching show significant speed improvements. With the aid of digital and analog quantum simulations, fermionic and many-body systems can be efficiently modelled. These simulations solve problems classical computation does not. In order to develop scalable, universal quantum processors, various platforms are being used, including superconducting circuits, trapped ions, and photonic qubits. As a result of error correction, reliable computation, and measurement-based methods, gate errors and decoherence are reduced. With established protocols like BB84, quantum cryptography protects communication. Using theoretical foundations, experimental results, and practical applications, this paper examines the interrelationships between computational complexity, quantum hardware, and information security. The results highlight the potential of quantum computing to change computation, simulation, and secure communication, creating a path for future scalable quantum technologies.