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T-Count Optimization of Quantum Carry Look-Ahead Adder

Vladislav Khalus

Published May 30, 2019• 0 citations
Publisher

Abstract

With the emergence of quantum physics and computer science in the 20th century, a new era was born which can solve very difficult problems in a much faster rate or problems that classical computing just can't solve. In the 21st century, quantum computing needs to be used to solve tough problems in engineering, business, medical, and other fields that required results not today but yesterday. To make this dream come true, engineers in the semiconductor industry need to make the quantum circuits a reality. To realize quantum circuits and make them scalable, they need to be fault tolerant, therefore Clifford+T gates need to be implemented into those circuits. But the main issue is that in the Clifford+T gate set, T gates are expensive to implement. Carry Look-Ahead addition circuits have caught the interest of researchers because the number of gate layers encountered by a given qubit in the circuit (or the circuit's depth) is logarithmic in terms of the input size n. Therefore, this thesis focuses on optimizing previous designs of out-of-place and in-place Carry Look-Ahead Adders to decrease the T-count, sum of all T and T Hermitian transpose gates in a quantum circuit.

DOI
10.13023/etd.2019.227

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With the emergence of quantum physics and computer science in the 20th century, a new era was born which can solve very difficult problems in a much faster rate or problems that classical computing just can't solve. In the 21st century, quantum computing needs to be used to solve tough problems in engineering, business, medical, and other fields that required results not today but yesterday. To make this dream come true, engineers in the semiconductor industry need to make the quantum circuits a reality. To realize quantum circuits and make them scalable, they need to be fault tolerant, therefore Clifford+T gates need to be implemented into those circuits. But the main issue is that in the Clifford+T gate set, T gates are expensive to implement. Carry Look-Ahead addition circuits have caught the interest of researchers because the number of gate layers encountered by a given qubit in the circuit (or the circuit's depth) is logarithmic in terms of the input size n. Therefore, this thesis focuses on optimizing previous designs of out-of-place and in-place Carry Look-Ahead Adders to decrease the T-count, sum of all T and T Hermitian transpose gates in a quantum circuit.
Quantum circuits of arithmetic operations such as addition are needed to implement quantum algorithms in hardware. Quantum circuits based on Clifford+T gates are used as they can be made tolerant to noise. The tradeoff of gaining fault tolerance from using Clifford+T gates and error correcting codes is the high implementation overhead of the T gate. As a result, the T-count performance measure has become important in quantum circuit design. Due to noise, the risk for errors in a quantum circuit computation increases as the number of gate layers (or depth) in the circuit increases. As a result, low depth circuits such as quantum carry lookahead adders (QCLA)s have caught the attention of researchers. This work presents two QCLA designs each optimized with emphasis on T-count or qubit cost respectively. In-place and out-of-place versions of each design are shown. The proposed QCLAs are compared against the existing works in terms of T-count. The proposed QCLAs for out-of-place addition achieve average T gate savings of 54.34%54.34 \%54.34% and 37.21%37.21 \%37.21%, respectively. The proposed QCLAs for in-place addition achieve average T gate savings of 72.11%72.11 \%72.11% and 35.87%35.87 \%35.87%
Progress in quantum hardware design is progressing toward machines of sufficient size to begin realizing quantum algorithms in disciplines such as encryption and physics. Quantum circuits for addition are crucial to realize many quantum algorithms on these machines. Ideally, quantum circuits based on fault-tolerant gates and error-correcting codes should be used as they tolerant environmental noise. However, current machines called Noisy Intermediate Scale Quantum (NISQ) machines cannot support the overhead associated with fault-tolerant design. In response, low depth circuits such as quantum carry lookahead adders (QCLA)s have caught the attention of researchers. The risk for noise errors and decoherence increase as the number of gate layers (or depth) in the circuit increases. This work presents an out-of-place QCLA based on Clifford+T gates. The QCLAs optimized for T gate count and make use of a novel uncomputation gate to save T gates. We base our QCLAs on Clifford+T gates because they can eventually be made fault-tolerant with error-correcting codes once quantum hardware that can support fault-tolerant designs becomes available. We focus on T gate cost as the T gate is significantly more costly to make fault-tolerant than the other Clifford+T gates. The proposed QCLAs are compared and shown to be superior to existing works in terms of T-count and therefore the total number of quantum gates. Finally, we illustrate the application of the proposed QCLAs in quantum image processing by presenting quantum circuits for bilinear interpolation.
Progress in quantum hardware design is progressing toward machines of sufficient size to begin realizing quantum algorithms in disciplines such as encryption and physics. Quantum circuits for addition are crucial to realize many quantum algorithms on these machines. Ideally, quantum circuits based on fault-tolerant gates and error-correcting codes should be used as they tolerant environmental noise. However, current machines called Noisy Intermediate Scale Quantum (NISQ) machines cannot support the overhead associated with faulttolerant design. In response, low depth circuits such as quantum carry lookahead adders (QCLA)s have caught the attention of researchers. The risk for noise errors and decoherence increase as the number of gate layers (or depth) in the circuit increases. This work presents an out-of-place QCLA based on Clifford+T gates. The QCLAs optimized for T gate count and make use of a novel uncomputation gate to save T gates. We base our QCLAs on Clifford+T gates because they can eventually be made faulttolerant with error-correcting codes once quantum hardware that can support fault-tolerant designs becomes available. We focus on T gate cost as the T gate is significantly more costly to make faulttolerant than the other Clifford+T gates. The proposed QCLAs are compared and shown to be superior to existing works in terms of T-count and therefore the total number of quantum gates. Finally, we illustrate the application of the proposed QCLAs in quantum image processing by presenting quantum circuits for bilinear interpolation.
Quantum circuits of many qubits are extremely difficult to realize; thus, the number of qubits is an important metric in a quantum circuit design. Further, scalable and reliable quantum circuits are based on fault tolerant implementations of quantum gates such as Clifford+T gates. An efficient quantum circuit saves quantum hardware resources by reducing the number of T gates without substantially increasing the number of qubits. This work presents a T-count optimized quantum circuit for integer multiplication with only 4 · n + 1 qubits and no garbage outputs. The proposed quantum multiplier design reduces the T-count by using a novel quantum conditional adder circuit. Also, where one operand to the conditional adder is zero, the conditional adder is replaced with a Toffoli gate array to further save T gates. Average T-count savings of 46:12, 47:55, 62:71 and 26.30 percent are achieved compared to the recent works by Kotiyal et al., Babu, Lin et al., and Jayashree et al., respectively.
Qutrit (or ternary) structures arise naturally in many quantum systems, particularly in certain non-abelian anyon systems. We present efficient circuits for ternary reversible and quantum arithmetics. Our main result is the derivation of circuits for two families of ternary quantum adders, namely ripple carry adders and carry look-ahead adders. The main difference to the binary case is the more complicated form of the ternary carry, which leads to higher resource counts for implementations over a universal ternary gate set. Our ternary ripple adder circuit has a circuit depth of O(n)O(n)O(n) and uses only 111 ancilla, making it more efficient in both, circuit depth and width than previous constructions. Our ternary carry lookahead circuit has a circuit depth of only O(log⁡ n)O(\log\,n)O(logn), while using with O(n)O(n)O(n) ancillas. Our approach works on two levels of abstraction: at the first level, descriptions of arithmetic circuits are given in terms of gates sequences that use various types of non-Clifford reflections. At the second level, we break down these reflections further by deriving them either from the two-qutrit Clifford gates and the non-Clifford gate C(X):∣i,j⟩↦∣i,j+δi,2mod  3⟩C(X): |i,j\rangle \mapsto |i, j + δ_{i,2} \mod 3\rangleC(X):∣i,j⟩↦∣i,j+δi,2​mod3⟩ or from the two-qutrit Clifford gates and the non-Clifford gate $P_9=\mbox{diag}(e^{-2 π\, i/9},1,e^{2 π\, i/9})$. The two choices of elementary gate sets correspond to two possible mappings onto two different prospective quantum computing architectures which we call the metaplectic and the supermetaplectic basis, respectively. Finally, we develop a method to factor diagonal unitaries using multi-variate polynomial over the ternary finite field which allows to characterize classes of gates that can be implemented exactly over the supermetaplectic basis.
Quantum computing (Q-computing) is a revolutionary technology that applies quantum mechanics (QM) to implement calculations significantly quicker than traditional computers. Q-computing employs Q-bits (qubits) rather than classical bits, which can take on a superposition state, making it possible to represent both 0 and 1 at once. This distinctive property allows qubits to perform multiple calculations simultaneously, making Q computers exponentially more powerful as more qubits are added, compared to the linear scaling of classical computers. However, challenges such as qubit instability and error rates remain significant obstacles to fully realizing this potential. A vital aspect of this technology is the development of Q arithmetic circuits, which act as the foundational blocks for efficiently executing Q algorithms. Q half-adder and full-adder circuits are integral to performing fundamental arithmetic operations within Q computers. In contrast to classical adders, Q adders rely on Q gates such as Controlled NOT (CNOT) and Toffoli gates. These gates exploit Q phenomena like entanglement and superposition, allowing for more efficient computations. The Q half-adder consists of two qubits and adds two single bits, producing a carry and sum output. It utilizes the CNOT gate to compute the sum and the Toffoli gate (controlled-controlled-NOT [CCNOT]) to compute the carry. The Q full-adder builds on this, adding three qubits to produce a sum and a carry output, further increasing computational capacity. Through the entanglement of qubits, these circuits allow for more parallelism and speed compared to classical adders. Q carry-look-ahead adders (QCLAs) and Q ripple-carry adders (QRCAs) are used to perform more complex arithmetic operations based on these half-adder and full-adder structures. Q arithmetic circuits have broad applications, boosting secure key generation in cryptography, speeding up matrix operations for faster model training in machine learning, and enabling more precise, efficient image transformations in Q image processing, benefiting fields like medical imaging and computer vision.