scholarly journals Estimating Gibbs partition function with quantum Clifford sampling

2022 ◽  
Author(s):  
Yusen Wu ◽  
Jingbo B Wang
Keyword(s):  
Partition Function ◽  
Spectral Gap ◽  
Sampling Technique ◽  
Quantum Circuit ◽  
Quantum Systems ◽  
Quantum Circuits ◽  
Partition Functions ◽  
Stochastic Matrices ◽  
Many Body ◽  
Quantum Devices

Abstract The partition function is an essential quantity in statistical mechanics, and its accurate computation is a key component of any statistical analysis of quantum system and phenomenon. However, for interacting many-body quantum systems, its calculation generally involves summing over an exponential number of terms and can thus quickly grow to be intractable. Accurately and efficiently estimating the partition function of its corresponding system Hamiltonian then becomes the key in solving quantum many-body problems. In this paper we develop a hybrid quantumclassical algorithm to estimate the partition function, utilising a novel Clifford sampling technique. Note that previous works on quantum estimation of partition functions require O(1/ε√∆)-depth quantum circuits [17, 23], where ∆ is the minimum spectral gap of stochastic matrices and ε is the multiplicative error. Our algorithm requires only a shallow O(1)-depth quantum circuit, repeated O(n/ε2) times, to provide a comparable ε approximation. Shallow-depth quantum circuits are considered vitally important for currently available NISQ (Noisy Intermediate-Scale Quantum) devices.

scholarly journals Free partition functions and an averaged holographic duality

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Nima Afkhami-Jeddi ◽  
Henry Cohn ◽  
Thomas Hartman ◽  
Amirhossein Tajdini
Keyword(s):  
Partition Function ◽  
Spectral Gap ◽  
Central Charge ◽  
Three Dimensional ◽  
Two Dimensions ◽  
Three Dimensions ◽  
Partition Functions ◽  
General Constraints ◽  
Dimensional Gravity ◽  
Holographic Duality

Abstract We study the torus partition functions of free bosonic CFTs in two dimensions. Integrating over Narain moduli defines an ensemble-averaged free CFT. We calculate the averaged partition function and show that it can be reinterpreted as a sum over topologies in three dimensions. This result leads us to conjecture that an averaged free CFT in two dimensions is holographically dual to an exotic theory of three-dimensional gravity with U(1)c×U(1)c symmetry and a composite boundary graviton. Additionally, for small central charge c, we obtain general constraints on the spectral gap of free CFTs using the spinning modular bootstrap, construct examples of Narain compactifications with a large gap, and find an analytic bootstrap functional corresponding to a single self-dual boson.

scholarly journals Analysis and limitations of modified circuit-to-Hamiltonian constructions

Quantum ◽  
2018 ◽  
Vol 2 ◽  
pp. 94 ◽  
Author(s):  
Johannes Bausch ◽  
Elizabeth Crosson
Keyword(s):  
Upper Bound ◽  
Ground State ◽  
Spectral Gap ◽  
General Setting ◽  
Quantum Circuit ◽  
Many Body ◽  
Graph Diameter ◽  
Uniform Distributions ◽  
Labeled Graphs ◽  
Constant Output

Feynman's circuit-to-Hamiltonian construction connects quantum computation and ground states of many-body quantum systems. Kitaev applied this construction to demonstrate QMA-completeness of the local Hamiltonian problem, and Aharanov et al. used it to show the equivalence of adiabatic computation and the quantum circuit model. In this work, we analyze the low energy properties of a class of modified circuit Hamiltonians, which include features like complex weights and branching transitions. For history states with linear clocks and complex weights, we develop a method for modifying the circuit propagation Hamiltonian to implement any desired distribution over the time steps of the circuit in a frustration-free ground state, and show that this can be used to obtain a constant output probability for universal adiabatic computation while retaining theΩ(T−2)scaling of the spectral gap, and without any additional overhead in terms of numbers of qubits.Furthermore, we establish limits on the increase in the ground energy due to input and output penalty terms for modified tridiagonal clocks with non-uniform distributions on the time steps by proving a tightO(T−2)upper bound on the product of the spectral gap and ground state overlap with the endpoints of the computation. Using variational techniques which go beyond theΩ(T−3)scaling that follows from the usual geometrical lemma, we prove that the standard Feynman-Kitaev Hamiltonian already saturates this bound. We review the formalism of unitary labeled graphs which replace the usual linear clock by graphs that allow branching and loops, and we extend theO(T−2)bound from linear clocks to this more general setting. In order to achieve this, we apply Chebyshev polynomials to generalize an upper bound on the spectral gap in terms of the graph diameter to the context of arbitrary Hermitian matrices.

scholarly journals WPG-Controlled Quantum BDD Circuits with BDD Architecture on GaAs-Based Hexagonal Nanowire Network Structure

2012 ◽  
Vol 2012 ◽  
pp. 1-6
Author(s):  
Hong-Quan ZHao ◽  
Seiya Kasai
Keyword(s):  
Quantum Logic ◽  
Quantum Circuit ◽  
Quantum Circuits ◽  
Combinational Circuit ◽  
Quantum Devices ◽  
Binary Decision ◽  
One Dimensional ◽  
Nanowire Network ◽  
Dimensional Electron Gas ◽  
Very High

One-dimensional nanowire quantum devices and basic quantum logic AND and OR unit on hexagonal nanowire units controlled by wrap gate (WPG) were designed and fabricated on GaAs-based one-dimensional electron gas (1-DEG) regular nanowire network with hexagonal topology. These basic quantum logic units worked correctly at 35 K, and clear quantum conductance was achieved on the node device, logic AND circuit unit, and logic OR circuit unit. Binary-decision-diagram- (BDD-) based arithmetic logic unit (ALU) is realized on GaAs-based regular nanowire network with hexagonal topology by the same fabrication method as that of the quantum devices and basic circuits. This BDD-based ALU circuit worked correctly at room temperature. Since these quantum devices and circuits are basic units of the BDD ALU combinational circuit, the possibility of integrating these quantum devices and basic quantum circuits into the BDD-based quantum circuit with more complicated structures was discussed. We are prospecting the realization of quantum BDD combinational circuitries with very small of energy consumption and very high density of integration.

scholarly journals Many-body thermodynamics on quantum computers via partition function zeros

2021 ◽  
Vol 7 (34) ◽  
pp. eabf2447
Author(s):  
Akhil Francis ◽  
Daiwei Zhu ◽  
Cinthia Huerta Alderete ◽  
Sonika Johri ◽  
Xiao Xiao ◽  
...  
Keyword(s):  
Phase Transitions ◽  
Partition Function ◽  
Quantum Computers ◽  
Partition Functions ◽  
Chain Model ◽  
Many Body ◽  
Partition Function Zeros ◽  
Many Body Systems ◽  
Classical Computing ◽  
Function Zeros

Partition functions are ubiquitous in physics: They are important in determining the thermodynamic properties of many-body systems and in understanding their phase transitions. As shown by Lee and Yang, analytically continuing the partition function to the complex plane allows us to obtain its zeros and thus the entire function. Moreover, the scaling and nature of these zeros can elucidate phase transitions. Here, we show how to find partition function zeros on noisy intermediate-scale trapped-ion quantum computers in a scalable manner, using the XXZ spin chain model as a prototype, and observe their transition from XY-like behavior to Ising-like behavior as a function of the anisotropy. While quantum computers cannot yet scale to the thermodynamic limit, our work provides a pathway to do so as hardware improves, allowing the future calculation of critical phenomena for systems beyond classical computing limits.

scholarly journals Fisher Information in Noisy Intermediate-Scale Quantum Applications

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 539
Author(s):  
Johannes Jakob Meyer
Keyword(s):  
Fisher Information ◽  
Quantum Algorithms ◽  
Quantum Fisher Information ◽  
Quantum Systems ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Quantum Devices ◽  
Intermediate Scale ◽  
Quantum Sensing ◽  
Near Term

The recent advent of noisy intermediate-scale quantum devices, especially near-term quantum computers, has sparked extensive research efforts concerned with their possible applications. At the forefront of the considered approaches are variational methods that use parametrized quantum circuits. The classical and quantum Fisher information are firmly rooted in the field of quantum sensing and have proven to be versatile tools to study such parametrized quantum systems. Their utility in the study of other applications of noisy intermediate-scale quantum devices, however, has only been discovered recently. Hoping to stimulate more such applications, this article aims to further popularize classical and quantum Fisher information as useful tools for near-term applications beyond quantum sensing. We start with a tutorial that builds an intuitive understanding of classical and quantum Fisher information and outlines how both quantities can be calculated on near-term devices. We also elucidate their relationship and how they are influenced by noise processes. Next, we give an overview of the core results of the quantum sensing literature and proceed to a comprehensive review of recent applications in variational quantum algorithms and quantum machine learning.

scholarly journals Clifford recompilation for faster classical simulation of quantum circuits

Quantum ◽  
2019 ◽  
Vol 3 ◽  
pp. 170
Author(s):  
Hammam Qassim ◽  
Joel J. Wallman ◽  
Joseph Emerson
Keyword(s):  
Fault Tolerant ◽  
State Of The Art ◽  
Quantum Circuit ◽  
Quantum Circuits ◽  
Monte Carlo Algorithm ◽  
Quantum Devices ◽  
Output State ◽  
Classical Simulation ◽  
Main Technique ◽  
Near Term

Simulating quantum circuits classically is an important area of research in quantum information, with applications in computational complexity and validation of quantum devices. One of the state-of-the-art simulators, that of Bravyi et al, utilizes a randomized sparsification technique to approximate the output state of a quantum circuit by a stabilizer sum with a reduced number of terms. In this paper, we describe an improved Monte Carlo algorithm for performing randomized sparsification. This algorithm reduces the runtime of computing the approximate state by the factorℓ/m, whereℓandmare respectively the total and non-Clifford gate counts. The main technique is a circuit recompilation routine based on manipulating exponentiated Pauli operators. The recompilation routine also facilitates numerical search for Clifford decompositions of products of non-Clifford gates, which can further reduce the runtime in certain cases by reducing the 1-norm of the vector of expansion,‖a‖1. It may additionally lead to a framework for optimizing circuit implementations over a gate-set, reducing the overhead for state-injection in fault-tolerant implementations. We provide a concise exposition of randomized sparsification, and describe how to use it to estimate circuit amplitudes in a way which can be generalized to a broader class of gates and states. This latter method can be used to obtain additive error estimates of circuit probabilities with a faster runtime than the full techniques of Bravyi et al. Such estimates are useful for validating near-term quantum devices provided that the target probability is not exponentially small.

scholarly journals Exponential quantum speed-ups are generic

2013 ◽  
Vol 13 (11&12) ◽  
pp. 901-924
Author(s):  
Fernando G.S.L. Brandao ◽  
Michal Horodecki
Keyword(s):  
Quantum Circuit ◽  
Black Box ◽  
Quantum Circuits ◽  
Query Complexity ◽  
Many Body ◽  
Many Body Theory ◽  
Exponential Separation ◽  
Local Quantum ◽  
Bounded Error ◽  
Body Theory

A central problem in quantum computation is to understand which quantum circuits are useful for exponential speed-ups over classical computation. We address this question in the setting of query complexity and show that for almost any sufficiently long quantum circuit one can construct a black-box problem which is solved by the circuit with a constant number of quantum queries, but which requires exponentially many classical queries, even if the classical machine has the ability to postselect. We prove the result in two steps. In the first, we show that almost any element of an approximate unitary 3-design is useful to solve a certain black-box problem efficiently. The problem is based on a recent oracle construction of Aaronson and gives an exponential separation between quantum and classical post-selected bounded-error query complexities. In the second step, which may be of independent interest, we prove that linear-sized random quantum circuits give an approximate unitary 3-design. The key ingredient in the proof is a technique from quantum many-body theory to lower bound the spectral gap of local quantum Hamiltonians.

scholarly journals ON THE GAP OF HAMILTONIANS FOR THE ADIABATIC SIMULATION OF QUANTUM CIRCUITS

2013 ◽  
Vol 11 (07) ◽  
pp. 1350063 ◽  
Author(s):  
ANAND GANTI ◽  
ROLANDO SOMMA
Keyword(s):  
Upper Bound ◽  
Spectral Gap ◽  
Quantum Circuit ◽  
Quantum Circuits ◽  
Search Problem ◽  
Adiabatic Evolution ◽  
Unstructured Search ◽  
Time Quantum ◽  
The Cost ◽  
The Impact

The time or cost of simulating a quantum circuit by adiabatic evolution is determined by the spectral gap of the Hamiltonians involved in the simulation. In "standard" constructions based on Feynman's Hamiltonian, such a gap decreases polynomially with the number of gates in the circuit, L. Because a larger gap implies a smaller cost, we study the limits of spectral gap amplification in this context. We show that, under some assumptions on the ground states and the cost of evolving with the Hamiltonians (which apply to the standard constructions), an upper bound on the gap of the order 1/L follows. In addition, if the Hamiltonians satisfy a frustration-free property, the upper bound is of the order 1/L2. Our proofs use recent results on adiabatic state transformations, spectral gap amplification, and the simulation of continuous-time quantum query algorithms. They also consider a reduction from the unstructured search problem, whose lower bound in the oracle cost translates into the upper bounds in the gaps. The impact of our results is that improving the gap beyond that of standard constructions (i.e. 1/L2), if possible, is challenging.

scholarly journals On the Expressibility and Overfitting of Quantum Circuit Learning

2021 ◽  
Vol 2 (2) ◽  
pp. 1-24
Author(s):  
Chih-Chieh Chen ◽  
Masaya Watabe ◽  
Kodai Shiba ◽  
Masaru Sogabe ◽  
Katsuyoshi Sakamoto ◽  
...  
Keyword(s):  
Performance Improvement ◽  
Quantum Circuit ◽  
Quantum Circuits ◽  
High Dimensional ◽  
Supporting Evidence ◽  
Generalization Error ◽  
Vc Dimension ◽  
Learning Problem ◽  
Quantum Devices ◽  
Function Approximator

Applying quantum processors to model a high-dimensional function approximator is a typical method in quantum machine learning with potential advantage. It is conjectured that the unitarity of quantum circuits provides possible regularization to avoid overfitting. However, it is not clear how the regularization interplays with the expressibility under the limitation of current Noisy-Intermediate Scale Quantum devices. In this article, we perform simulations and theoretical analysis of the quantum circuit learning problem with hardware-efficient ansatz. Thorough numerical simulations show that the expressibility and generalization error scaling of the ansatz saturate when the circuit depth increases, implying the automatic regularization to avoid the overfitting issue in the quantum circuit learning scenario. This observation is supported by the theory on PAC learnability, which proves that VC dimension is upper bounded due to the locality and unitarity of the hardware-efficient ansatz. Our study provides supporting evidence for automatic regularization by unitarity to suppress overfitting and guidelines for possible performance improvement under hardware constraints.

scholarly journals Layerwise learning for quantum neural networks

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Andrea Skolik ◽  
Jarrod R. McClean ◽  
Masoud Mohseni ◽  
Patrick van der Smagt ◽  
Martin Leib
Keyword(s):  
Learning Strategy ◽  
Quantum Circuit ◽  
Quantum Circuits ◽  
Quantum Devices ◽  
Error Surface ◽  
Effective Training ◽  
One Step ◽  
Near Term ◽  
Lower Test ◽  
Learning Schemes

AbstractWith the increased focus on quantum circuit learning for near-term applications on quantum devices, in conjunction with unique challenges presented by cost function landscapes of parametrized quantum circuits, strategies for effective training are becoming increasingly important. In order to ameliorate some of these challenges, we investigate a layerwise learning strategy for parametrized quantum circuits. The circuit depth is incrementally grown during optimization, and only subsets of parameters are updated in each training step. We show that when considering sampling noise, this strategy can help avoid the problem of barren plateaus of the error surface due to the low depth of circuits, low number of parameters trained in one step, and larger magnitude of gradients compared to training the full circuit. These properties make our algorithm preferable for execution on noisy intermediate-scale quantum devices. We demonstrate our approach on an image-classification task on handwritten digits, and show that layerwise learning attains an 8% lower generalization error on average in comparison to standard learning schemes for training quantum circuits of the same size. Additionally, the percentage of runs that reach lower test errors is up to 40% larger compared to training the full circuit, which is susceptible to creeping onto a plateau during training.

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