037 - 2.1 Dolev Bluvstein | NotionNext BLOG

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https://www.youtube.com/watch?v=g8TMpaMBMa4&list=WL&type=snipo

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http://arxiv.org/abs/2312.03982 based on v1

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Completed

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QEC23

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00:44:14

Neutral atom quantum computer architecture:

The FPGA processes images from the camera real-time and in this work sends control signals to the Raman 2D AOD for local single-qubit control.

SLM 将激光分成上千条光束，可以控制上千个原子。 87 Rb，常用于激光技术中。

acousto-optic deflectors

create dynamically programmable rectangular array of light

parallel sorting of atoms: from original configuration to 400-atom defect free array

The Levine-Pichler CZ entangling gate with global control

The Levine-Pichler CZ entangling gate with global control is a special case of C-phase gates available in Rydberg atoms. This gate is implemented by bringing two atoms within a blockade radius, where they perform a two-qubit gate when illuminated by a Rydberg laser[2]. The Rydberg laser is global in the sense that it illuminates all the qubits[2].

The implementation of this gate involves the following steps:

Bring two qubits within the blockade radius, ensuring that they are both illuminated by the Rydberg laser[2].

Apply a sequence of optimal control pulses to achieve high-fidelity entanglement[1].

Characterize the gate fidelity by comparing the experimentally measured fidelity with the ideal fidelity. For example, the fidelity of the entangling gate was found to be 99.52(4)% in one study[1].

These methods demonstrate the potential of neutral-atom quantum computing in implementing high-fidelity and efficient double-bit gates, paving the way for advancements in quantum computation.

Citations: [1] https://www.nature.com/articles/s41586-023-06481-y [2] https://dl.acm.org/doi/pdf/10.1145/3508352.3549331 [3] https://link.aps.org/doi/10.1103/PhysRevLett.123.170503 [4] https://inspirehep.net/literature/2166146 [5] https://arxiv.org/abs/1908.06101v2

blockade radius

The blockade radius in systems involving Rydberg atoms, is a critical concept. It refers to a specific distance around a Rydberg-excited atom within which another atom cannot be similarly excited to a Rydberg state. This phenomenon is known as the Rydberg blockade. Here are some key points about the blockade radius:

Rydberg Blockade Mechanism: When an atom is excited to a Rydberg state, it has a large electric dipole moment due to its highly excited electron. This large dipole moment can significantly affect the energy levels of nearby atoms. As a result, if another atom is within a certain distance (the blockade radius), the energy required to excite it to the same Rydberg state becomes significantly different. This energy shift effectively prevents the second atom from being excited if the laser light used is tuned to the original Rydberg state's excitation energy.

Dependence on Rydberg State and Interaction Strength: The size of the blockade radius depends on the specific Rydberg state and the interaction strength between the atoms. Typically, higher Rydberg states with more excited electrons lead to a larger blockade radius due to stronger dipole-dipole or van der Waals interactions.

Significance in Quantum Computing: In quantum computing, particularly in quantum gates that use neutral atoms, the Rydberg blockade mechanism is essential. It enables the entanglement of atoms and the implementation of quantum gates like the Controlled-NOT (CNOT) gate. By exploiting the blockade, one can control the quantum state of one atom based on the state of another, a fundamental requirement for quantum logic operations.

Experimental Considerations: The exact value of the blockade radius is crucial for designing and implementing quantum gates in Rydberg atom-based quantum computers. It defines how closely atoms can be packed and how they can be manipulated for effective quantum operations.

The blockade radius is not just a theoretical concept; it has been observed and measured in various experimental setups involving cold Rydberg atoms. This phenomenon is a cornerstone of the field of Rydberg atom quantum computing and is a focus of ongoing research to develop more efficient and scalable quantum computing technologies.

https://link.aps.org/doi/10.1103/PhysRevLett.123.170503

https://www.nature.com/articles/s41586-023-06481-y

The blockade radius in Rydberg atom systems, which is crucial for the Rydberg blockade mechanism in quantum computing, varies depending on the specific atomic states and experimental conditions. Generally, the blockade radius is determined by the strength of the interaction between the Rydberg atoms compared to the Rabi frequency of the system. The blockade radius can be calculated using the formula , where is the van der Waals interaction coefficient and is the Rabi frequency.

In typical experiments involving Rydberg atoms, the blockade radius is often found to be in the range of 4 to 10 um. This distance is sufficient to enable the controlled interactions necessary for quantum computing operations, such as entangling qubits, without affecting neighboring atoms outside this radius.

Furthermore, research has shown that the Rydberg blockade radius can be significantly enhanced under certain conditions. For instance, when the principal quantum numbers of the Rydberg states differ significantly, the blockade radius can be substantially increased, surpassing 50 micrometers in some cases. This enhancement of the blockade radius expands the potential for larger-scale quantum operations and long-range quantum entanglement, which are essential for advancing quantum technologies.

The blockade radius's size is a key factor in determining the scalability and efficiency of quantum communication and computation systems based on Rydberg atoms. By manipulating the blockade radius, researchers can optimize the performance of quantum gates and entanglement processes in neutral atom quantum computers.

https://en.wikiversity.org/wiki/Rydberg_Atoms/Rydberg_blockade

https://pubmed.ncbi.nlm.nih.gov/38017846/

The blockade radius in neutral atomic quantum computing refers to the minimum distance between two atoms required for them to be in the Rydberg state and perform a two-qubit gate. Typical values for the blockade radius are 2 to 3 lattice sites, which corresponds to a next-nearest-neighbor connectivity in a square lattice[3]. This means that two atoms must be within this radius to be able to interact and perform the desired quantum gate.

Citations: [1] https://pennylane.ai/qml/demos/tutorial_neutral_atoms/ [2] https://dl.acm.org/doi/pdf/10.1145/3508352.3549331 [3] https://epjquantumtechnology.springeropen.com/articles/10.1140/epjqt/s40507-023-00190-1

Atomic Rydberg state

Atomic Rydberg states are highly excited bound states of a Coulomb potential, characterized by large principal quantum numbers (typically n ≥ 30). These states have properties that scale with the principal quantum number n, and are significantly enhanced compared to ground or near ground states[1][5].

Rydberg states of an atom or molecule are electronically excited states with energies that follow the Rydberg formula as they converge on an ionic state. The wave functions of high Rydberg states are very diffuse and span diameters that approach infinity. As a result, any isolated neutral molecule behaves like a hydrogen-like atom at the Rydberg limit[2].

A Rydberg atom is an excited atom with one or more electrons that have a very high principal quantum number n. The higher the value of n, the farther the electron is from the nucleus, on average. Rydberg atoms have a number of peculiar properties including an exaggerated response to electric fields, long decay periods, and electron wavefunctions that approximate, under some conditions, classical orbits of electrons about the nuclei[4].

Rydberg states have been used in various applications in atomic, molecular, and optical physics. They are also of interest in the study of quantum control and quantum information processing due to their strong interactions and long lifetimes[3][6].

Citations: [1] https://www.sciencedirect.com/topics/physics-and-astronomy/rydberg-state [2] https://en.wikipedia.org/wiki/Rydberg_state [3] http://www.phys.ttu.edu/~gglab/rydberg_state.html [4] https://en.wikipedia.org/wiki/Rydberg_atom [5] https://www.sciencedirect.com/topics/chemistry/rydberg-state [6] https://www.phys.uconn.edu/~rcote/Projects/Rydberg/Rydberg.html [7] https://www.chemeurope.com/en/encyclopedia/Rydberg_state.html [8] https://arc-alkali-rydberg-calculator.readthedocs.io/en/latest/Rydberg_atoms_a_primer_notebook.html

pairs of atoms in tweezers

put everything in the cluster state. 1st layer of CZ gates. by global Rydberg laser.

reconfigure half of atoms and shift them over by changing this one voltage waveform, second Rydberg laser.

2 year ago, 2Q gate fidelity ~97.5%

2Q gate fidelity has improved. 99.54(2)%

full programmable, parallel 1Q gates. 99.91%

Any arbitrary single qubit rotation on any an atom or qubit

Achieving single qubit operations in neutral atomic quantum computing typically involves manipulating the state of individual atoms using finely controlled laser pulses. The process is quite sophisticated and relies on the unique properties of neutral atoms, particularly when they are in highly controlled environments like optical traps or lattices. Here's an overview of how single qubit operations are typically achieved:

Laser Cooling and Trapping: Atoms are first cooled to near absolute zero temperatures using laser cooling techniques. They are then trapped in optical lattices or tweezers, which are arrays of tightly focused laser beams that create potential wells to hold individual atoms in place.

Addressing Individual Atoms: Using high-resolution imaging and targeting systems, lasers can be focused precisely on individual atoms. This allows for the selective manipulation of the state of each atom without affecting its neighbors.

State Manipulation with Laser Pulses: The internal state of an atom (which represents the qubit) can be manipulated using laser pulses. These pulses can be tuned to specific frequencies that correspond to the energy differences between the quantum states of the atom. By carefully controlling the duration, intensity, and frequency of these pulses, the quantum state of the atom can be precisely controlled.

Rydberg State Excitation for Enhanced Control: In many neutral atom quantum computing setups, atoms are excited to Rydberg states, where one of the atom's electrons is excited to a very high energy level. Rydberg atoms have exaggerated quantum properties, such as larger electric dipole moments, which make them more sensitive to electromagnetic fields and thus easier to control with laser beams.

Implementation of Quantum Gates: Single qubit quantum gates, such as the Pauli-X, Y, Z gates, or the Hadamard gate, are implemented by inducing coherent rotations of the qubit's state. These rotations are achieved by the precise timing and shaping of the laser pulses.

Error Correction and Detection: Due to factors like atomic motion, laser frequency instability, and environmental noise, performing accurate single qubit operations is challenging. Advanced techniques, including error detection and correction protocols, are used to mitigate these issues and improve the fidelity of the operations.

Performing a single-qubit operation involves several steps and components:

Physical Qubits Encoding: Physical qubits are encoded in clock states within the ground-state hyperfine manifold of atoms, stored in optical tweezer arrays created by a spatial light modulator (SLM). This setup allows for up to 280 atomic qubits, which are utilized for high-fidelity operations (page 2).

Utilization of Raman Excitation: Single-qubit rotations are achieved through Raman excitation. This is done by illuminating chosen atoms using a pair of crossed acousto-optic deflectors (AODs). The focused beam waist is large enough to be robust against fluctuations in atomic positions (page 13).

Local Single-Qubit Gates: To enable individual single-qubit gates, the same Raman laser system used for global rotation is employed. This is done by illuminating only selected atoms with a focused beam (page 13).

Programmable Operations: The entire circuit is defined by the appropriate trapping SLM phase profile, along with waveforms for several Arbitrary Waveform Generator (AWG) channels and a TTL pulse generator. This allows for programming complex circuits on hundreds of physical qubits (page 13).

Error Prevention and Correction: Techniques such as dynamical decoupling (using global Raman pulses) and error correction are employed to maintain qubit coherence and accuracy throughout the process (pages 2, 12).

Control Infrastructure: The control infrastructure consists of several AWGs, which are synchronized to less than 10-ns jitter. These AWGs are used for various purposes like IQ control of a 6.8 GHz source, pulse-shaping of global and local Raman driving, and controlling the positions of atoms during the circuit (page 12).

This process illustrates the complex interplay of optical, electronic, and quantum mechanical systems required to perform single-qubit operations in this advanced quantum computing architecture.

3 种 zones，需要测量的移到 readout zone，这不影响在entangle zone和storage zone的qubits。

16 data qubits are fixed.

8 ancilla qubits.

Circuit is simply programmed by specifying SLM profile and AOD waveform Parallel control over many qubits with O(1) classical controls

优势：逻辑操作可以并行

Transversal gates 例如：

Transversal single-qubit gate

Transversal entangling gate Shor 1996, Dennis et al 2001

Inherently fault-tolerant - d rounds of correction not required between each gate

Long-range, direct connections between logical qubits - can have significant savings for large-scale algorithms

Efficient control: all physical qubits receive the same instruction and act like one big atom

Conventional decoding

d ↑ → infidelity ↑ , fidelity worse

Correlated decoding

Correlated decoding is a sophisticated method for decoding information from quantum systems, specifically when dealing with entangled qubits in error-correcting codes like surface codes. This approach takes into account the correlations between errors in entangled qubits to improve the accuracy of decoding.

Concept of Correlated Decoding: It involves understanding how physical errors propagate between qubit pairs during operations like transversal CNOT gates. This propagation creates correlations that can be utilized for improved decoding, especially in logical qubits encoded in surface codes [page 3].

Hypergraph Construction for Decoding: The process starts by constructing a decoding hypergraph based on a description of the logical algorithm. This hypergraph's vertices correspond to stabilizer measurement results, and each edge or hyperedge represents a physical error mechanism that affects the stabilizers it connects [page 14].

Decoding Algorithm and Edge Weights: A decoding algorithm uses the hypergraph, along with each experimental snapshot, to find the most likely physical error consistent with the measurements. The edge weights in the hypergraph are related to the probability of each error [page 14].

Handling Errors During Transversal CNOT: Correlated decoding is particularly useful when dealing with errors that occur before or after transversal CNOT operations. For instance, if errors occur before a transversal CNOT, they can propagate and double the density of errors on the target logical qubit. Correlated decoding can effectively handle such scenarios [page 18].

Improvement Over Conventional Decoding: Correlated decoding is shown to be more robust than conventional decoding methods like minimum-weight perfect matching within codes. This is because it accounts for the correlations arising from deterministic error propagation [page 3].

Application in Quantum Error Correction: Correlated decoding is vital in quantum error correction, particularly in logical qubit algorithms with transversal gates. It helps in accurately identifying and correcting errors, thus enhancing the overall fidelity and performance of quantum circuits [pages 16, 18].

In summary, correlated decoding is a method that improves the accuracy of decoding in quantum systems by utilizing the correlations between errors in entangled qubits, especially in the context of quantum error correction codes like surface codes. It is more effective than traditional decoding methods in handling complex error patterns, particularly in scenarios involving operations like transversal CNOT gates.

d ↑ → infidelity ↓, fidelity better

M. Cain et al., “Correlated decoding of logical algorithms with transversal gates,” Mar. 2024, Accessed: Mar. 09, 2024. [Online]. Available: http://arxiv.org/abs/2403.03272

Figure 4. Circuit illustrating the structure of an [[n,k,d]] stabilizer code.

for each stabilizer ,

From the above, we see that

if the stabilizer commutes with an error the measurement of ancilla qubit returns ‘0’.

If the stabilizer anti-commutes with an error , the measurement returns ‘1’.

When two logical qubits do a gate, add edges/hyperedges to their decoding graph THEORY RESULTS:

d rounds per CNOT → ~O(1) rounds

Works for Cliffords and non-Cliffords

[1]D. Gottesman, “The Heisenberg Representation of Quantum Computers.” arXiv, Jul. 01, 1998. Accessed: Feb. 04, 2023. [Online]. Available: http://arxiv.org/abs/quant-ph/9807006

Key observation: when performing logical algorithms, instead of considering individual logical qubits, consider quantum algorithms as a whole - (see also spacetime decoding)

Delfosse, N. & Paetznick, A. Spacetime codes of Clifford circuits (2023). arXiv:2304.05943v2.

接下来执行transversal CNOT,

由于双比特门原生的是CZ门，所以前后加transversal H 门，可以等效。

[[7,1,3]] steane code or called d = 3 color code

with the useful capability of transversal operations of the full Clifford group: Hadamard (H), π/2 phase (S) gate, and CNOT

parallel logical operations

time cost for the readout and feedforward operations : 800 us << 2 s coherence time

Why 3D code

One important challenge in realizing complex algorithms with logical qubits is that universal computation cannot be implemented transversally [42]. For instance, when using 2D codes such as the surface code, non-Clifford operations cannot be easily performed [37], and relatively expensive techniques are required for nontrivial computation [24, 43] as Clifford circuits can be easily simulated [44]. In contrast, 3D codes can transversally realize non-Clifford operations, but lose the transversal H [37].

The smallest interesting colour code

What is the smallest interesting colour code? The first possible answer is the 7 qubit Steane code. Except, it isn’t especially interesting. In particular, the transversal gates of the Steane…

https://earltcampbell.com/2016/09/26/the-smallest-interesting-colour-code/

Vasmer, Kubica PRX Quantum 2022 See also arXiv:2309.08663, arXv:2309.09893

一个 code 有 8个physical qubits，3 个logical qubits。

要48 个 logical qubits，意味着有16个 codes，也就是需要128 个physical qubits。

code 内部的三个logical qubits 可以作用transversal CCZ gates.

transversal CNOT between blocks

transversal {CCZ, CZ, Z} gates on the logical qubits encoded within each block

intrablock CNOTs by physical permutation

减少了相干错误

error detection: 去掉了无效数据，提高了XEB

XEB

Cross-entropy benchmarking (XEB) is a method that uses the properties of random quantum programs to determine the fidelity of a wide variety of circuits. It can characterize the performance of a large quantum device and be used to accurately characterize qubit interactions, potentially leading to better calibration

cross-entropy benchmarking (XEB), a larger value typically indicates higher fidelity or better performance of a quantum system. XEB is used to determine the fidelity of a wide variety of circuits, and when applied to circuits with many qubits, it can characterize the performance of a large quantum device. Therefore, a larger XEB value suggests that the quantum system is performing more accurately and with higher fidelity[1].

Citations: [1] https://quantumai.google/cirq/noise/qcvv/xeb_theory [2] https://www.osti.gov/servlets/purl/1783613 [3] https://www.hpcwire.com/2023/12/11/qubit-roundup-quantum-zoo-grows-rigettis-qpu-play-googles-new-algorithm-queras-ec-advance-and-more/

Cross-Entropy Benchmarking (XEB) is indeed a critical tool in quantum computing for assessing the performance of quantum processors, particularly in the realm of demonstrating quantum computational advantage and benchmarking quantum processors. The value of XEB, as understood from the sources, indicates the fidelity of the quantum state preparation.

When considering the value of XEB, it's essential to understand that a perfect, noiseless quantum computer would yield an XEB value of 1. On the other hand, a value of 0 indicates that the samples could have been obtained via random guessing, suggesting that the quantum computer is too noisy and has no significant advantage over classical computations[1].

The interpretation that a larger XEB value indicates higher fidelity or better performance seems to align with the understanding that a value closer to 1 (a larger value) would indeed suggest a more accurate and high-fidelity quantum system. This understanding is crucial, especially when considering quantum supremacy, where surpassing a certain threshold of XEB value indicates an advantage over classical computing capabilities.

However, it is also important to consider the context and the specific method of XEB being employed. The literature suggests that the relationship between XEB values and quantum system performance can be complex, especially in regimes of high noise or specific circuit architectures [2].

In summary, while a larger XEB value (closer to 1) generally suggests higher fidelity and better performance of a quantum system, the exact interpretation can depend on various factors, including the noise level, circuit architecture, and specific characteristics of the quantum gates used. The understanding of XEB and its implications for quantum system performance is nuanced and can vary depending on the specific circumstances of its application.

[1]https://en.wikipedia.org/wiki/Cross-Entropy_benchmarking

[2]https://quics.umd.edu/publications/sharp-phase-transition-linear-cross-entropy-benchmarking

提高了XEB 10 倍以上，代价是测量增加了所需时间。

Seven-dimensional hypercube circuit:

Scrambling circuit with 48 logical qubits using the [[8,3,2]] code (Figs. 5, 6). Eight [[8,3,2]] code blocks, arranged in two rows of four blocks, are encoded with 3 layers of entangling gates, followed by three transversal CNOTs. This is repeated with eight further codes (originally in the storage zone) before a final transversal CNOT between the two groups, forming 4-dimensional hypercube connectivity between the 48 logical qubit triplets, or a 7-dimensional physical hypercube connectivity.

上面是 entangling zone

下面是 storage zone

The main use of two-copy measurements

Two-copy measurements using logical circuits are a concept primarily used in the field of quantum computing and quantum information theory. The main use of two-copy measurements in this context includes:

Quantum State Tomography: This is the process of reconstructing the quantum state of a system. By using two-copy measurements, it's possible to estimate the properties of a quantum state with higher accuracy. This is particularly important in quantum computing, where knowing the precise state of qubits is crucial for computation and error correction.

Entanglement Detection: Two-copy measurements can be used to detect entanglement between quantum states. Entanglement is a fundamental aspect of quantum mechanics where pairs or groups of particles interact in such a way that the quantum state of each particle cannot be described independently of the state of the others. Detecting and measuring this entanglement is crucial for many quantum computing and quantum information processing tasks.

Error Correction: In quantum computing, error correction is vital due to the susceptibility of quantum states to decoherence and other types of errors. Two-copy measurements can be used to implement certain quantum error correction protocols more efficiently, helping to maintain the integrity of quantum information over longer periods.

Quantum Information Processing: These measurements can be used in various quantum information processing tasks, such as quantum cryptography and quantum communication protocols, where the security and fidelity of information transfer are paramount.

Benchmarking Quantum Devices: Two-copy measurements can be used to benchmark the performance of quantum devices. By comparing the outcomes of these measurements with theoretical predictions, one can gauge the accuracy and reliability of quantum processors and other quantum devices.

In summary, two-copy measurements with logical circuits are a powerful tool in the realm of quantum technology, providing enhanced capabilities for state tomography, entanglement detection, error correction, and overall quantum information processing.

使用逻辑电路进行的两份测量是量子计算和量子信息理论领域中主要使用的概念。在这个背景下，两份测量的主要用途包括：

量子态重构：这是重建系统的量子态的过程。通过使用两份测量，可以更准确地估计量子态的性质。这在量子计算中特别重要，因为了解量子比特的精确状态对于计算和错误校正至关重要。

纠缠检测：两份测量可以用于检测量子态之间的纠缠。纠缠是量子力学的基本特征，其中粒子的成对或成组相互作用，使得每个粒子的量子态不能独立地描述。检测和测量这种纠缠对于许多量子计算和量子信息处理任务至关重要。

错误校正：在量子计算中，由于量子态容易受到退相干和其他类型的错误的影响，错误校正是至关重要的。两份测量可以用于更高效地实现某些量子错误校正协议，有助于在较长时间内保持量子信息的完整性。

量子信息处理：这些测量可以用于各种量子信息处理任务，比如量子密码学和量子通信协议，其中信息传输的安全性和保真度至关重要。

量子设备基准测试：两份测量可以用于基准测试量子设备的性能。通过将这些测量的结果与理论预测进行比较，可以评估量子处理器和其他量子设备的准确性和可靠性。

总之，使用逻辑电路进行的两份测量是量子技术领域中的强大工具，为态重构、纠缠检测、错误校正和整体量子信息处理提供了增强的能力。

The main use of two-copy measurements is particularly in measuring the purity or entanglement entropy of quantum states.. Here are the key aspects and applications:

Measuring Purity and Entanglement Entropy: Two-copy measurements are used to calculate the purity or entanglement entropy of a quantum state. This involves Bell basis measurements between two copies of the same state. Such measurements are crucial in quantum information theory to understand the degree of entanglement and the purity of quantum states (page 22).

Extracting Information about Pauli Strings: Two-copy measurements can simultaneously extract information about all 4^N Pauli strings. This property is used in an analysis technique known as Bell difference sampling to experimentally evaluate and directly verify the amount of additive Bell magic in quantum circuits. This measurement of magic is associated with non-Clifford operations and quantifies the number of T gates required to realize the quantum state (page 8).

Error Mitigation Techniques: Combining encoded qubits and two-copy measurement allows for additional error mitigation techniques. This approach helps in extrapolating expectation values to cases of unit-purity, thereby evaluating the averaged Pauli expectation values with relative precision (page 8).

Evaluating Quantum Circuit Performance: Two-copy measurements are used to assess the performance of quantum circuits. For example, they assist in calculating measures of distance from stabilizer states and in evaluating the contribution of various elements to the overall performance of a quantum circuit (pages 22, 27).

In summary, two-copy measurements in the field of quantum computing serve as a powerful method for analyzing and measuring critical properties of quantum states and circuits, such as purity, entanglement entropy, and the effectiveness of error mitigation strategies. These measurements are integral to understanding and improving the performance of quantum processors.

Control over single logical qubits as the fundamental units can dramatically reduce costs of a logical processor

通过对单个逻辑量子比特的控制，可以大幅降低逻辑处理器的成本

correlated decoding ( spacetime decoding 相关)

Instead of considering individual logical qubits, consider algorithms as a whole (e.g. correlated decoding)

不是考虑单个逻辑量子比特，而是将算法作为一个整体来考虑（例如相关解码）。

需要重新思考逻辑qubit和之前算法中的qubits之间的关系，它们的行为并不是完全相同。

（有种从模拟计算到数字计算的转变意思，虽然局限了计算的变化性，但是离散的门会表现更好）

可以探索逻辑层面的算法。

—>~100 logical qubits

quantum low-density-parity-check (qLDPC) codes

[54] Bravyi, S. et al. High-threshold and low-overhead fault tolerant quantum memory (2023). arXiv:2308.07915v1.

[55] Xu, Q. et al. Constant-Overhead Fault-Tolerant Quantum Computation with Reconfigurable Atom Arrays arXiv:2308.08648v1.

Experimentation with early generation logical devices will likely reshape the way we think these large-scale processors should be built (theory & hardware)

主要的问题：

atom loss 主要由于gate。目前来说，移动atoms的行为导致的atom loss得到了改善。

main causes of atomic loss in neutral atomic quantum computing

In neutral atomic quantum computing, the main cause of atomic loss is not due to the instability of the atom's nucleus, as in radioactivity. Instead, atomic loss is primarily due to the following reasons:

Sporadic atom loss: Neutral atom systems are prone to occasional atom loss, which can be mitigated through efficient adaptation to this loss[2].

Gate errors: Errors in entangling operations mediated through Rydberg interactions can lead to atomic loss. Most errors are Z-type and loss/leakage-type errors[7].

Scalability challenges: As the number of qubits increases, maintaining high-fidelity gate operations and reducing errors becomes more challenging. This can result in atomic loss due to the inability to scale the system effectively[8].

To mitigate these challenges, researchers have proposed various coping strategies at the hardware and software levels, such as mid-circuit measurement and quantum error correction[6][7]. These techniques can help detect and correct errors in real-time, improving the overall performance and stability of neutral atomic quantum computers.

Citations: [1] https://pennylane.ai/qml/demos/tutorial_neutral_atoms/ [2] https://arxiv.org/pdf/2111.06469.pdf [3] https://epjquantumtechnology.springeropen.com/articles/10.1140/epjqt/s40507-023-00190-1 [4] https://iopscience.iop.org/article/10.1088/0953-4075/49/20/202001/ampdf [5] https://pubs.aip.org/physicstoday/article-abstract/70/7/44/926355/Quantum-computing-with-neutral-atomsWith-their?redirectedFrom=fulltext [6] https://atom-computing.com/atom-computing-demonstrates-key-milestone-on-path-to-fault-tolerance/ [7] https://www.nature.com/articles/s41586-023-06481-y [8] https://physicsworld.com/a/atomic-quantum-processors-make-their-debut/

目前不能重复测量，measurement is destructive. 想要解决这个问题的方案是未来使用新的辅助qubits。测量用时～500 us

challenges

In neutral atom quantum computing, the inability to reset and reuse ancilla qubits that have been measured, as opposed to what's possible in superconducting quantum computing, stems from fundamental differences in the physical systems and the methods used to manipulate and measure qubits in these platforms.

Physical State of Qubits: In neutral atom systems, qubits are typically individual atoms held in place by optical traps. When a measurement is performed on these atoms, it often involves an interaction that fundamentally alters their state (such as a photon absorption and re-emission process), which leads to the collapse of the quantum state. Resetting these atoms to their original quantum state for reuse as ancilla qubits is not straightforward and can be a complex process that requires additional operations.

Measurement Techniques: The techniques used to measure the state of qubits in neutral atom systems often involve processes that are inherently destructive. For instance, fluorescence measurement, a common technique used, involves detecting light emitted by an atom when it transitions between energy levels. This process typically leaves the atom in a different state than it was initially.

System Reinitialization Challenges: After measurement, reinitializing neutral atoms to a specific quantum state (e.g., ground state) for reuse requires complex manipulation. This might include using laser cooling and other techniques to return the atoms to a desired state, which can be technically challenging and time-consuming.

Contrast with Superconducting Qubits: Superconducting qubits, on the other hand, are macroscopic circuits that can often be reset more easily. The state of a superconducting qubit can be manipulated using microwave pulses, and after measurement, these qubits can be brought back to their ground state relatively quickly, allowing for their reuse.

Technical and Engineering Challenges: The difference also reflects the technical and engineering challenges specific to each type of quantum computing platform. Superconducting and neutral atom systems each have unique advantages and constraints, which lead to different capabilities and limitations, particularly in terms of qubit manipulation and measurement.

In summary, the challenges associated with resetting and reusing measured ancilla qubits in neutral atom quantum computing arise from the intrinsic properties of the qubits, the nature of the measurement processes involved, and the technical complexities of manipulating individual atomic states. These challenges highlight the diverse nature of quantum computing technologies and the ongoing need for innovation and development in this field.

DiVincenzo 5 准则中第2点：

“2. The ability to initialize the state of the qubits to a simple fiducial state, such as |000…〉” (DiVincenzo 和 IBM, 2000, p. 3)