Recently, various quantum computing and communication tasks have been implemented using IBM's superconductivity-based quantum computers which are available on the cloud. Here, we show that the circuits used in most of those works were not optimized and the use of the optimized circuits can considerably improve the possibility of observing unique features of quantum mechanics. Specifically, a systematic procedure is used here to obtain optimized circuits (circuits having reduced gate count and number of levels) for a large number of Clifford+T circuits which have already been implemented in the IBM quantum computers. Optimized circuits implementable in IBM quantum computers are also obtained for a set of reversible benchmark circuits. With a clear example, it is shown that the reduction in circuit costs enhances the fidelity of the output state (with respect to the theoretically expected state in the absence of noise) as lesser number of gates and levels introduce lesser amount of errors during evolution of the state. Further, considering Mermin inequality as an example, it's shown that the violation of classical limit is enhanced when we use an optimized circuit. Thus, the approach adopted here can be used to identify relatively weaker signature of quantumness and also to establish quantum supremacy in a stronger manner.
Recently, various quantum computing and communication tasks have been implemented using IBM's superconductivity-based quantum computers which are available on the cloud. Here, we show that the circuits used in most of those works were not optimized and the use of the optimized circuits can considerably improve the possibility of observing unique features of quantum mechanics. Specifically, a systematic procedure is used here to obtain optimized circuits (circuits having reduced gate count and number of levels) for a large number of Clifford+T circuits which have already been implemented in the IBM quantum computers. Optimized circuits implementable in IBM quantum computers are also obtained for a set of reversible benchmark circuits. With a clear example, it is shown that the reduction in circuit costs enhances the fidelity of the output state (with respect to the theoretically expected state in the absence of noise) as lesser number of gates and levels introduce lesser amount of errors during evolution of the state. Further, considering Mermin inequality as an example, it's shown that the violation of classical limit is enhanced when we use an optimized circuit. Thus, the approach adopted here can be used to identify relatively weaker signature of quantumness and also to establish quantum supremacy in a stronger manner.
Recently, various quantum computing and communication tasks have been implemented using IBM’s superconductivity-based quantum computers. Here, we show that the circuits used in most of those works were not optimized and obtain the corresponding optimized circuits. Optimized circuits implementable in IBM quantum computers are also obtained for a set of reversible benchmark circuits. With a clear example, it is shown that the reduction in circuit cost enhances the fidelity of the output state (with respect to the theoretically expected state in the absence of noise) as fewer gates and less circuit depth introduce fewer errors during evolution of the state. Further, considering Mermin inequality as an example, it is shown that the violation of the classical limit is enhanced when we use optimized circuits. Thus, the present approach can be used to identify a relatively weaker signature of quantumness and to establish quantum supremacy in a stronger manner.
IBM has made several quantum computers available to researchers around the world via cloud services. Two architectures with five qubits, one with 16, and one with 20 qubits are available to run experiments. The IBM architectures implement gates from the Clifford+T gate library. However, each architecture only implements a subset of the possible CNOT gates. In this paper, we show how Clifford+T circuits can efficiently be mapped into the two IBM quantum computers with 5 qubits. We further present an algorithm and a set of circuit identities that may be used to optimize the Clifford+T circuits in terms of gate count and number of levels. It is further shown that the optimized circuits can considerably reduce the gate count and number of levels and thus produce results with better fidelity.
For practical usage of quantum systems in solving real-world problems, large amounts of classical data are required to be transferred/encoded to the quantum domain. Arbitrary classical data is usually encoded onto quantum devices by synthesizing and initializing a corresponding quantum state. Current techniques of arbitrary state synthesis, however, produce deep and complex quantum circuits, leading to low state fidelity and possible violations of decoherence constraints. In this work, we propose an improved methodology and optimized circuits for synthesizing any arbitrary quantum state from given classical data. Compared to existing methods, the proposed methodology results in circuits with lower gate count, lower circuit depth, and high state fidelity. The proposed methods are evaluated by simulation in MATLAB and IBM qasm, and realistic implementation on an IBM quantum device. The experimental results show a reduction in gate count and circuit depth by a factor of two over existing methods.
Quantum computers are a revolutionary class of computational platforms with applications in combinatorial and global optimization, machine learning, and other domains involving computationally hard problems. While these machines typically operate on qubits—quantum information elements that can occupy superpositions of the basis∣0⟩and∣1⟩states—recent advances have demonstrated the practical implementation of higher-dimensional quantum systems (qudits) across various hardware platforms. In these hardware realizations, the higher-order states are less stable and thus remain coherent for a shorter duration than the basis∣0⟩and∣1⟩states. Moreover, formal methods for designing efficient encoder circuits for these systems remain underexplored. This limitation motivates the development of efficient circuit techniques for qudit systems (d-level quantum systems). Previous works have typically established generating gate sets for higher-dimensional codes by generalizing the methods used for qubits. In this work, we introduce a systematic framework for optimizing encoder circuits for prime-dimension stabilizer codes. This framework is based on novel generating gate sets whose elements map directly to efficient Clifford gate sequences. We demonstrate the effectiveness of this method on key codes, achieving a 13–44% reduction in encoder circuit gate count for the qutrit (d = 3)[[9,5,3]]3,[[5,1,3]]3, and[[7,1,3]]3codes, and a 9–21% reduction for the ququint (d = 5)[[10,6,3]]5code when compared to prior work. We also achieved circuit depth reductions up to 42%.
Quantum computing is an emerging technology that combines the principles of both computer science and quantum mechanics to solve computationally challenging problems significantly faster than the current classical computers. In this thesis, a proof of concept to generate hardware-executable quantum circuits for Noisy Intermediate-Scale Quantum (NISQ) devices that follow the paradigm of approximate computing is presented. We adopt a multi-level optimization approach and consider the placement of native quantum gates that can be physically implemented on one of the existing quantum systems (IBM, Rigetti) as a circuit topology optimization problem and the adjustment of parameters of these native quantum gates as a continuous design optimization problem. The outer topology problem is solved with the aid of a genetic algorithm, whereas the gradient-descent method is used for the inner design optimization. Our approach starts from the reference circuit and transforms it into an executable circuit with tunable parameters by replacing the high-level quantum operations with a set of approximate decompositions, e.g., single qubit rotation quantum gates or a combination of single qubit rotation gates (matrix multiplication). Later, the inner design optimization ensures that the circuit created is tuned to be executed to achieve an expectation value close to that of the reference circuit. This is complemented by compiler-based optimizations to further reduce or aggregate the quantum gates of the optimized circuit. This three-step pipeline is embedded into an outer genetic algorithm framework that inspects many different circuit designs (the approximate-decomposition replacements are by no means unique) and returns a set of unique approximate quantum circuits that can be executed on hardware. We have tested our circuit generation approach for superconducting quantum systems such as IBM and Rigetti hardware for many different benchmark circuits such as Quantum Fourier Transform, Toffoli, quantum adder, multi-controlled operations and three oracle-based algorithms, namely, Grover's search algorithm, Deutsch and Bernstein-Vazirani algorithm. In nearly all cases, our approach outperforms the quantum compiler frameworks by IBM and Rigetti even on their highest optimization level and produces significantly smaller circuits, up to 2x reduction in the number of gates. In addition, the circuits generated using the proposed approach provide better (a) performance (on average, improved by 24.25%) and (b) reliability (on average, improved by 23.50%) compared to the IBM generated circuits when executed on the ibmq_5_yorktown physical quantum device.
While quantum computing holds great potential in combinatorial optimization, electronic structure calculation, and number theory, the current era of quantum computing is limited by noisy hardware. Many quantum compilation approaches can mitigate the effects of imperfect hardware by optimizing quantum circuits for objectives such as critical path length. Few approaches consider quantum circuits in terms of the set of vendor-calibrated operations (i.e., native gates) available on target hardware. This manuscript expands the analytical and numerical approaches for optimizing quantum circuits at this abstraction level. We present a procedure for combining the strengths of analytical native gate-level optimization with numerical optimization. Although we focus on optimizing Toffoli gates on the IBMQ native gate set, the methods presented are generalizable to any gate and superconducting qubit architecture. Our optimized Toffoli gate implementation demonstrates an 18% reduction in infidelity compared with the canonical implementation as benchmarked on IBM Jakarta with quantum process tomography. Assuming the inclusion of multi-qubit cross-resonance (MCR) gates in the IBMQ native gate set, we produce Toffoli implementations with only six multi-qubit gates, a 25% reduction from the canonical eight multi-qubit implementations for linearly connected qubits.