Abstract
The efficient compiling of arbitrary single-qubit gates into a sequence of gates from a finite gate set is of fundamental importance in quantum computation. The exact bounds of this compilation are given by the Solovay–Kitaev theorem, which serves as a powerful tool in compiling quantum algorithms that require many qubits. However, the inverse closure condition it imposes on the gate set adds a certain complexity to the experimental compilation, making the process less efficient. This was recently resolved by a version of the Solovay–Kitaev theorem for inverse-free gate sets, yielding a significant gain. Considering the recent progress in the field of three-level quantum systems, in which qubits are replaced by qutrits, it is possible to achieve the quantum speedup guaranteed by the Solovay–Kitaev theorem simply from orthogonal gates. Nevertheless, it has not been investigated previously whether the condition of inverse closure can be relaxed for these qutrit-based orthogonal compilations as well. In this work, we answer this positively, by obtaining improved Solovay–Kitaev approximations to an arbitrary orthogonal qutrit gate, with an accuracy from a sequence of orthogonal gates taken from an inverse-free set.
MSC:
81P68; 81P65; 20C35
1. Introduction
Qutrit-based quantum computation [1,2,3] is an emerging trend in the field of quantum computing. In contrast to two-level quantum systems used in standard quantum computing, three-level quantum systems are used in qutrit-based computing. Accordingly, a qubit that has basis states and is replaced by a qutrit having three basis states, , and . A growing interest in qutrit-based computations can be found in the literature, and they have been proven to provide a better platform for quantum communication [4,5].
In standard quantum computation, a qubit undergoes a state change after being operated by a quantum gate [6]. This gate is a unitary matrix of unit determinants (due to normalization factors), boiling down the problem into the action of an element in , the special unitary group. Thus, it would be the group , the special unitary group, that defines the action of a quantum gate applied on a qutrit. However, once the physical implementation is considered, there are several advantages in confining to orthogonal gates [7], as the fault-tolerant implementation of the complex phase gate is much more complicated than the orthogonal gates [8]. In this regard, qutrit-based computations with gates in the special orthogonal group are of particular importance, and this has been mathematically investigated in detail in [7].
Once the orthogonal gates are considered, we should know how we can approximate an arbitrary quantum gate by means of a finite sequence of elements taken from that gate set efficiently, as far as both the time and space complexities are concerned. In standard quantum computing, this problem has been answered by Solovay [9] and Kitaev [10] by establishing the remarkable theorem known today as the Solovay–Kitaev theorem. According to this theorem, it is possible to approximate an arbitrary unitary with a unit determinant by a product of physically realizable basic gates to an arbitrary accuracy [11,12]. It was shown in [7] that the Solovay–Kitaev theorem applies for qutrit-based orthogonal computations.
Once the applicability of the Solovay–Kitaev theorem to orthogonals in is verified, the next concern is the feasibility. In this regard, reducing noise [13] and quantum Hamiltonian complexity [14] is of particular importance. These tasks can be more easily accomplished by lifting the assumption on the essential inclusion of inverses in the Solovay–Kitaev theorem [15]. This left an open question in standard quantum computation, until it was resolved very recently by Bouland and Giurgica-Tiron [16], with a clever algorithmic procedure for efficiently approximating a unitary gate with an inverse-free gate set.
In this paper, we show that Bouland and Giurgica-Tiron scheme can be modified and applied for orthogonal computations as well, by proving an inverse–free version of the Solovay–Kitaev theorem in . Accordingly, the remainder of the paper is organised as follows: In Section 2, we present the basic definitions and mathematical tools required. Then, we single out the ingredient in the Solovay–Kitaev theorem that requires inverses, and present a proof and an algorithm with an inverse-free gate set for in Section 3. Our concluding remarks are found in Section 4.
2. Basic Definitions and Theorems
Definition 1
(Universal quantum gate set). A set of finite single-qubit unitary gates is called a set of universal gates if is dense in .
Notation 1.
For , .
Theorem 1
(Solovay–Kiteav). Let G be a finite set of elements in containing its own inverses, such that is dense in . Then, for any , provides an ε-net for where .
The highly constructive proof of this theorem relies on approximations of elements close to the identity. From a rough approximation to a given element element U, it finds a better approximation to by the repeated application of the following lemma, which is the most important ingredient in the proof.
Lemma 1
(Shrinking Lemma). Let be a finite set of elements in containing its own inverses such that is dense in . There exist constants with such that, for every : if is an -net for , then is an -net for .
The Solovay–Kitaev algorithm decomposes into a concatenation of four unitary matrices which make the group commutator - . When the gate set is inverse-closed, to approximate inverse elements as , one can reverse the order of the sequence of V-approximation and apply the corresponding inverses. The Bouland and Giurgica-Tiron scheme [16] uses -approximations to inverse elements instead of exact inverses, using the following lemmata. By we denote pauli operators.
Lemma 2
(Approximating the group commutator [16]). For two unitaries V and W such that and , assume and . Additionally, assume that and . Then,
Lemma 3
([16]). If , then the error is suppressed in the direction of X. Specifically, there are complex scalars of order such that
Lemma 4
([16]). If and , then the construction is an -approximation to the identity, i.e., .
Lemma 5
([16]). Assume that . Additionally, assume that given a unitary V, we have an ε-approximate inverse such that . Then, the construction is an -approximation to , i.e., .
Since is an -approximation to , we can use it for the execution of the Solovay–Kitaev algorithm, as it has yielded a tighter precision than Lemma 2. Accordingly, we focus on presenting a modified version of the shrinking lemma, which is the only portion of the Solovay–Kitaev theorem that makes use of inverses. Its proof, that we will present in Section 3, requires the following map:
Cornwell’s map The two-to-one mapping known as the Cornwell’s map is a homomorphism from to . It maps the element , where and , to
Lemma 6
([7]). For any two , if , then .
3. Results
3.1. Universal Sets in and
Lemma 7.
If is a universal set in , then the set is universal in SU(2).
Proof.
Let . Let be universal in . Then, is finite and is dense in . Hence, . Then, is finite. Let , then . such that,
where for some . By (1), we obtain the following results: and . We observe , which implies that . Furthermore, unitary invariance implies that
3.2. Modified Shrinking Lemma
Lemma 8.
Let be a finite set of elements in such that is dense in . There exists constants with , such that for every , if is an -net for , then is an -net for .
Proof.
Assume is an -net for for some . Following the steps of the standard proof, we first prove that
Let . Since U is a special unitary matrix, we can find such that . Since , . Following some computational steps, we can obtain . Since , , and using the Taylor expansion, we obtain . Choose , such that , and , such that . With , , we ensure that , . Since is an -net for , we can find , such that , . Since , , we can find , such that , , where , . Consequently, , . Since , from unitary invariance we obtain . Hence, , . Following a similar approach, we can find , such that , where , and thus , . Recall from Lemma 3 that , and hence . Therefore, we can approximate from elements of such that there exists where . Similarly, . Note that we can restate Pauli matrices in the form and .
Let
Then, from the Taylor expansion of the terms in and , we obtain and . Now, we prove that in can be approximated by elements in .
From the proof of the standard shrinking lemma,
Taking the second term of (4) as ,
Now we move to the latter part of the proof: . Let Since , . By the initial assumption, we know is an -net for . Then there exist such that , which implies . Now, since is a -net for , from the above proof we can find such that , where , thus U is approximated by a sequence of elements from . □
3.3. Inverse-Free Orthogonal Approximations
Theorem 2
(Inverse-free Solovay–Kitaev theorem in ). Let be a universal set in . Then, for any , provides an ε-net for where and .
Proof.
Let and . The surjectivity of Cornwell’s map guarantees the existence of such that . Since is a universal set in , from Lemma 7 we know that is universal in . Since the Solovay–Kiteav theorem holds in , we can obtain such that . From Lemma 6, Additionally, the homomorphism readily gives . Then, . Since , we have . Then, we can conclude that U can be approximated by , where and □
Now we provide an algorithmic procedure of approximating orthogonal matrices in with the use of a universal gate set of orthogonal matrices (Algorithm 1). The steps closely follow the ones in the algorithms in [7,16]. For detailed descriptions of the steps, the readers are encouraged to refer to those algorithms.
| Algorithm 1 Inverse-free Solovay–Kitaev algorithm in |
|
4. Concluding Remarks
The purpose of this study was to check the possibility of efficient and noiseless quantum computation with three-level quantum systems, for which an inverse-free version of the Solovay–Kitaev theorem could be of immense help. Following the previous work [7], we considered orthogonal gates instead of unitary gates. Accordingly, we used the inverse-free version of the Solovay–Kitaev theorem developed by Bouland and Giurgica-Tiron [16] and verified that a version of it is applicable to . We concluded that efficient orthogonal compiling is possible with a finite universal gate set which holds the mere condition of densely generating the orthogonal space . More specifically, we obtained and as the values for sequence length and run time for one such approximation of an orthogonal matrix in , confirming that Solovay-Kitaev executions are possible for orthogonals in with a universal gate set.
It is evident that we require a greater value for the exponent in the poly-logarithmic asymptotic of the algorithm than the one in the standard algorithm. The inverse construction approach we utilized yielded approximations to precision, whereas it only requires approximations to precision. It would be an interesting future task to investigate the possibility of lowering this value of the exponent in the poly-logarithmic asymptotic by producing approximations to the precision.
Author Contributions
Conceptualization and Methodology: A.M.; Formal Analysis and Original Draft Preparation: D.F.; Review and Validation: K.D.S. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
No data were used to support this study.
Conflicts of Interest
The authors declare no conflict of interest.
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