Span programs and quantum time complexity
- URL: http://arxiv.org/abs/2005.01323v1
- Date: Mon, 4 May 2020 08:43:14 GMT
- Title: Span programs and quantum time complexity
- Authors: Arjan Cornelissen and Stacey Jeffery and Maris Ozols and Alvaro
Piedrafita
- Abstract summary: We show how to convert a quantum algorithm for $f$ with time complexity $T$ into a span program for $f$ such that it compiles back into a quantum algorithm for $f$ with time complexity $widetildeO(T)$.
In particular, we show how to convert a quantum algorithm for $f$ with time complexity $T$ into a span program for $f$ such that it compiles back into a quantum algorithm for $f$ with time complexity $widetildeO(T)$.
- Score: 2.4182732872327186
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Span programs are an important model of quantum computation due to their
tight correspondence with quantum query complexity. For any decision problem
$f$, the minimum complexity of a span program for $f$ is equal, up to a
constant factor, to the quantum query complexity of $f$. Moreover, this
correspondence is constructive. A span program for $f$ with complexity $C$ can
be compiled into a bounded error quantum algorithm for $f$ with query
complexity $O(C)$, and vice versa.
In this work, we prove an analogous connection for quantum time complexity.
In particular, we show how to convert a quantum algorithm for $f$ with time
complexity $T$ into a span program for $f$ such that it compiles back into a
quantum algorithm for $f$ with time complexity $\widetilde{O}(T)$. While the
query complexity of quantum algorithms obtained from span programs is
well-understood, it is not generally clear how to implement certain
query-independent operations in a time-efficient manner. We show that for span
programs derived from algorithms with a time-efficient implementation, we can
preserve the time efficiency when implementing the span program. This means in
particular that span programs not only fully capture quantum query complexity,
but also quantum time complexity.
One practical advantage of being able to convert quantum algorithms to span
programs in a way that preserves time complexity is that span programs compose
very nicely. We demonstrate this by improving Ambainis's variable-time quantum
search result using our construction through a span program composition for the
OR function.
Related papers
- Sum-of-Squares inspired Quantum Metaheuristic for Polynomial Optimization with the Hadamard Test and Approximate Amplitude Constraints [76.53316706600717]
Recently proposed quantum algorithm arXiv:2206.14999 is based on semidefinite programming (SDP)
We generalize the SDP-inspired quantum algorithm to sum-of-squares.
Our results show that our algorithm is suitable for large problems and approximate the best known classicals.
arXiv Detail & Related papers (2024-08-14T19:04:13Z) - Accelerated Quantum Amplitude Estimation without QFT [0.0]
We put forward a Quantum Amplitude Estimation algorithm delivering superior performance (lower quantum computational complexity and faster classical computation parts) compared to the approaches available to-date.
The correctness of the algorithm and the $O(frac1varepsilon)$ bound on quantum computational complexity are supported by precise proofs.
arXiv Detail & Related papers (2024-07-23T18:49:11Z) - Quantum algorithms for Hopcroft's problem [45.45456673484445]
We study quantum algorithms for Hopcroft's problem which is a fundamental problem in computational geometry.
The classical complexity of this problem is well-studied, with the best known algorithm running in $O(n4/3)$ time.
Our results are two different quantum algorithms with time complexity $widetilde O(n5/6)$.
arXiv Detail & Related papers (2024-05-02T10:29:06Z) - Taming Quantum Time Complexity [45.867051459785976]
We show how to achieve both exactness and thriftiness in the setting of time complexity.
We employ a novel approach to the design of quantum algorithms based on what we call transducers.
arXiv Detail & Related papers (2023-11-27T14:45:19Z) - Near-Optimal Quantum Algorithms for Bounded Edit Distance and Lempel-Ziv
Factorization [2.684542790908823]
We present a quantum $tildeO(sqrtnk+k2)$-time algorithm that uses $tildeO(sqrtnz)$ queries, where $tildeO(cdot)$ hides polylogarithmic factors.
Our second main contribution is a quantum algorithm that achieves the optimal time complexity of $tildeO(sqrtnz)$.
arXiv Detail & Related papers (2023-11-03T09:09:23Z) - Quantum algorithms: A survey of applications and end-to-end complexities [90.05272647148196]
The anticipated applications of quantum computers span across science and industry.
We present a survey of several potential application areas of quantum algorithms.
We outline the challenges and opportunities in each area in an "end-to-end" fashion.
arXiv Detail & Related papers (2023-10-04T17:53:55Z) - Intermediate-qudit assisted Improved quantum algorithm for string
matching with an Advanced Decomposition of Fredkin gate [1.9798034349981157]
This article shows an improved quantum circuit implementation for the string-matching problem with the help of higher-dimensional intermediate temporary qudits.
It is also shown that with the help of intermediate qudits not only the complexity of depth can be reduced but also query complexity can be reduced for a quantum algorithm.
arXiv Detail & Related papers (2023-04-06T13:11:07Z) - Quantum Clustering with k-Means: a Hybrid Approach [117.4705494502186]
We design, implement, and evaluate three hybrid quantum k-Means algorithms.
We exploit quantum phenomena to speed up the computation of distances.
We show that our hybrid quantum k-Means algorithms can be more efficient than the classical version.
arXiv Detail & Related papers (2022-12-13T16:04:16Z) - Entanglement and coherence in Bernstein-Vazirani algorithm [58.720142291102135]
Bernstein-Vazirani algorithm allows one to determine a bit string encoded into an oracle.
We analyze in detail the quantum resources in the Bernstein-Vazirani algorithm.
We show that in the absence of entanglement, the performance of the algorithm is directly related to the amount of quantum coherence in the initial state.
arXiv Detail & Related papers (2022-05-26T20:32:36Z) - Variational learning algorithms for quantum query complexity [3.980076328494117]
We develop variational learning algorithms to study quantum query complexity.
We apply our method to analyze various cases of quantum query complexity.
Our method can be readily implemented on the near-term Noisy Intermediate-Scale Quantum (NISQ) devices.
arXiv Detail & Related papers (2022-05-16T05:16:15Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.