MicroCloud Hologram Inc. FPGA-Based High-Performance Surface Code Quantum Simulation Platform: Efficient Error Correction Algorithm Validation under Rotated Layout

MicroCloud Hologram (NASDAQ: HOLO) introduced an FPGA-based surface code quantum simulator optimized for rotated distance surface codes, claiming >5x speed vs GPU for distance-5 rotated codes and ~30% lower power consumption.

Rhea-AI Summary

MicroCloud Hologram (NASDAQ: HOLO) introduced an FPGA-based surface code quantum simulator optimized for rotated distance surface codes, claiming >5x speed vs GPU for distance-5 rotated codes and ~30% lower power consumption. The platform maps stabilizer measurement and MWPM decoding onto FPGA logic for real-time syndrome decoding and Monte Carlo error-rate estimation.

The simulator supports multiple noise models, real-time feedback, and fault-tolerant simulation features; the company cites cash reserves >3 billion RMB and plans to invest >400 million USD in frontier technologies including quantum computing.

Positive

• Simulation speed >5x vs GPU for distance-5 rotated codes
• Power reduction approximately 30% compared with GPU-based simulators
• Resource efficiency rotated surface code uses ~half the qubits versus standard layout
• Real-time feedback enabling immediate error-injection and debugging
• Planned investment over $400 million to advance quantum and related technologies

Negative

• Large cash deployment planned from >3 billion RMB reserves (> $400M investment)
• Performance claims are vendor benchmarks without third-party validation

Argus Feb 25 session

+4.13% close to close Open Argus

Details

News Market Reaction – HOLO

On Feb 25, the day this news came out, HOLO closed 4.13% above the previous close.

Data tracked by StockTitan Argus for the Feb 25 session.

Key Figures

Cash reserves: 3 billion RMB Planned investment: 400 million USD Distance-3 surface code size: 25 physical qubits +5 more

Cash reserves

3 billion RMB

Company-level cash reserves mentioned in article

Planned investment

400 million USD

Planned spend from reserves into blockchain, quantum, AI AR and related tech

Distance-3 surface code size

25 physical qubits

Distance-3 traditional surface code encoding one logical qubit

Performance vs GPU

5-fold speed increase

FPGA simulator vs GPU on distance-5 rotated codes

Power reduction vs GPU

30% reduction

FPGA simulator vs GPU power consumption

Current share price

$2.18

Pre-news price vs 52-week high of $60.00 and low of $2.02

52-week high discount

-96.37%

Price vs 52-week high before this news

1-day move

2.83%

Price change in prior 24h before article publication

Historical Context

5 past events · Latest: Feb 18

5 events

1. Feb 18

   Quantum consensus tech

   24h Move

   +0.0%

   Announced quantum fault-tolerant consensus algorithm and reiterated large cash reserves.

2. Feb 06

   Entangled state protocol

   24h Move

   +5.8%

   Unveiled GHZ/W state transmission scheme via Brownian state quantum channel.

3. Jan 16

   FPGA tensor networks

   24h Move

   +1.4%

   Detailed FPGA-accelerated tensor network computing for quantum spin models.

4. Jan 08

   Multi-FPGA QFT sim

   24h Move

   +2.0%

   Launched scalable multi-FPGA QFT simulator targeting larger quantum algorithms.

5. Jan 05

   Quantum spectral filter

   24h Move

   +7.9%

   Released learnable quantum spectral filter for hybrid graph neural networks.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Key Terms

fpga, surface code, quantum error correction, ancilla qubits, +3 more

7 terms

fpga technical

"developed a surface code quantum simulator based on FPGA."

A field-programmable gate array (FPGA) is a type of computer chip whose internal wiring can be changed after it is made, allowing engineers to program custom hardware functions without designing a new chip. For investors, FPGAs matter because that flexibility lets companies quickly adapt products to new software, standards, or customer needs—like a toolbox that can be rearranged to build different machines—so demand and pricing can shift with trends in data centers, telecommunications, AI, and specialized electronics.

surface code technical

"Quantum error correction is one of the core challenges... and the surface code, as an efficient..."

A surface code is a method used in quantum computing to detect and correct errors by arranging qubits in a grid where patterns of measurements reveal faults, much like a quilt pattern helping you spot and mend a torn patch. It matters to investors because robust error correction is a key hurdle to building practical, scalable quantum computers; progress or setbacks in surface-code implementations can materially affect a company’s technology roadmap, costs, timelines and competitive position.

quantum error correction technical

"Quantum error correction is one of the core challenges in realizing practical quantum computing"

Quantum error correction is a set of methods for detecting and fixing mistakes in quantum computers by encoding fragile quantum information across multiple physical parts, much like using multiple copies or checksums to protect a sensitive digital file. For investors, it matters because reliable error correction is a key technical milestone that determines whether quantum machines can scale from experimental devices to practical tools that could disrupt computing, encryption, drug discovery and other industries.

ancilla qubits medical

"The surface code arranges qubits in a two-dimensional grid and uses ancilla qubits to measure stabilizers"

Ancilla qubits are extra quantum bits used as helpers inside a quantum computer to perform tasks like detecting and correcting errors, checking computations, or extracting results without disturbing the main data. Think of them as spare hands or scratch paper that let a delicate calculation be tested and fixed without ruining the original work. For investors, the number and quality of ancilla qubits matter because they directly affect a machine’s reliability, useful workload size, and how quickly quantum systems can move from lab experiments to practical, scalable products.

minimum weight perfect matching technical

"HOLO adopts the Minimum Weight Perfect Matching (MWPM) algorithm to decode the syndrome."

A minimum weight perfect matching picks pairs from a network so every item is matched exactly once and the sum of the pairing costs is as small as possible. Imagine pairing up dancers on a floor so the total distance they walk is as little as possible. Investors care because the same idea is used to cut execution and settlement costs, match assets to liabilities, or route trades and allocations more efficiently, reducing expenses and operational risk.

monte carlo technical

"HOLO chose the Monte Carlo method to average multiple run instances"

A Monte Carlo simulation is a computer-based method that explores thousands of possible outcomes by randomly varying key inputs, like returns, interest rates, or costs, to show a range of likely results. For investors it reveals how uncertain factors can affect portfolio value or investment decisions—think of running many different “what if” scenarios, like rolling dice to see all the ways a plan could succeed or fail, so you can judge risk and potential reward.

linear feedback shift registers technical

"implemented through linear feedback shift registers (LFSR) to generate pseudo-random sequences."

A linear feedback shift register is a simple digital circuit that produces long sequences of bits by shifting data along a chain and feeding back selected outputs to form the next input, like a mechanical odometer where a few gears determine the next number. Investors should care because LFSRs are used in hardware random number generation, encryption, communications and chip testing; predictable or flawed designs can weaken product security, reliability and regulatory compliance, creating operational and reputational risk.

AI-generated analysis. How Rhea-AI works. Not financial advice.

See more from StockTitan in Google Search and AI answers. Adds StockTitan as a preferred source · opens Google

Add on Google Not now

SHENZHEN, China, Feb. 25, 2026 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, has developed a surface code quantum simulator based on FPGA. This innovative technology marks a new milestone in quantum error correction simulation, particularly with its optimized design targeted at rotated surface codes. As a company focused on quantum hardware and simulation solutions, the simulator launched this time fully leverages the unique advantages of FPGA (Field-Programmable Gate Array), including its highly parallel processing capability, reconfigurable hardware architecture, and exceptional computational performance. Quantum error correction is one of the core challenges in realizing practical quantum computing, and the surface code, as an efficient quantum error correction scheme, is highly favored due to its high threshold, scalability, and two-dimensional grid structure. However, traditional simulation methods are often limited by computational resources, making the simulation of large-scale surface codes extremely complex. HOLO's new simulator overcomes these bottlenecks through FPGA hardware acceleration, providing researchers and engineers with a real-time, high-fidelity simulation environment.

HOLO is committed to deeply integrating FPGA technology with quantum error correction algorithms. The core of this simulator lies in the precise modeling of rotated distance surface codes. The rotated distance surface code is a variant form that optimizes the arrangement of qubits by rotating the traditional surface code layout, thereby reducing the number of required physical qubits while maintaining high error correction capability. This design is particularly suitable for quantum systems with limited resources, as it can achieve equivalent error correction performance with a smaller code distance.

To understand the significance of this technology, it is first necessary to grasp the basic principles of quantum computing. Quantum computing utilizes the superposition and entanglement properties of quantum bits (qubits) to process information. Unlike classical bits, a qubit can exist in multiple states simultaneously, thereby enabling exponential computational acceleration. However, quantum systems are highly susceptible to noise interference, such as bit flips or phase errors, which can lead to unreliable computational results. Quantum error correction codes are specifically designed to address this issue by mapping logical qubits to multiple physical qubits through redundant encoding, thereby detecting and correcting errors. The surface code arranges qubits in a two-dimensional grid and uses ancilla qubits to measure stabilizers—these stabilizers are the defining operators of the code, used to identify errors without destroying the quantum information.

As an optimized version of the surface code, the rotated distance surface code further improves efficiency. In the traditional surface code, the code distance (distance) defines the number of errors the code can correct, typically requiring a square grid to achieve an odd-distance code. For example, a distance-3 surface code requires 25 physical qubits to encode one logical qubit. However, the rotated distance surface code achieves the same code distance with fewer qubits by rotating the grid by 45 degrees and adjusting the boundary conditions. Specifically, for a rotated code of distance d, it requires only (d²+ 1)/2 data qubits and (d²- 1)/2 ancilla qubits, saving nearly half the resources compared to the standard surface code. This saving is critically important in real quantum hardware, where the number of qubits on current quantum chips is limited and manufacturing costs are high. HOLO's simulator is specifically optimized for this rotated code, ensuring that the simulation process can accurately capture the unique error correction dynamics introduced by the rotated layout.

FPGA plays an indispensable role in this simulator. FPGA is a programmable hardware that allows users to customize circuit logic through hardware description languages (such as Verilog or VHDL). Unlike general-purpose processors, FPGA can execute multiple operations in parallel without the need for sequential scheduling. This makes it particularly suitable for simulating the parallel nature of quantum systems. In HOLO's implementation, the simulator maps the grid structure of the surface code onto the logic units (LUTs and FFs) of the FPGA. The state of each qubit is represented by a register group that stores its amplitude or probability information (in classical simulation, quantum states are typically represented by complex vectors). The core of the error correction algorithm—stabilizer measurement—is implemented as parallel circuit modules, which can simultaneously process the computations of multiple stabilizers, thereby accelerating the extraction of the error syndrome.

The technical implementation logic begins with the overall architecture. The hardware framework of the simulator is based on high-order FPGA chips, which provide millions of logic units and high-speed memory interfaces. First, HOLO designed a reconfigurable grid generator module that dynamically configures the surface code layout according to the user-input code distance and rotation parameters. For rotated distance codes, the grid is not a standard rectangle but a diamond or rotated square shape, with qubits on the boundaries optimized to reduce edge effects. The generator uses parameterized Verilog code to instantiate the qubit array, ensuring layout flexibility. Next is the state initialization module, which encodes the initial state of the logical qubit onto the physical qubits, including the application of X, Z, or Y gates to simulate initial errors or prepare entangled states.

The core of the simulation process is the error injection and error correction loop. HOLO's simulator supports a variety of noise models, such as depolarizing noise or bit-flip noise, which are implemented on the FPGA through random number generators. The random number generator utilizes the built-in true random sources of the FPGA (such as ring oscillators) to ensure the authenticity of the noise. After error injection, the ancilla qubits measure the stabilizers, and these measurements are executed in parallel: each stabilizer corresponds to a dedicated circuit path that computes the parity check. The measurement results form the error syndrome—a bit string that indicates the location and type of errors. Syndrome decoding is a key step in error correction, and HOLO adopts the Minimum Weight Perfect Matching (MWPM) algorithm to decode the syndrome. This algorithm is optimized into a parallel version on the FPGA, using variants to find matching paths, significantly reducing latency.

In the performance benchmark tests, HOLO's simulator stands out prominently. Compared to GPU-based simulators, it achieves more than a 5-fold speed increase when simulating distance-5 rotated codes, while reducing power consumption by 30%. This is because the dedicated circuits on FPGA avoid the general scheduling overhead of GPUs. More importantly, the simulator supports a real-time feedback loop, allowing users to inject custom error patterns and immediately observe the error correction effects, which is crucial for debugging quantum algorithms. For example, when simulating Shor's algorithm or Grover's search, surface code error correction can be seamlessly integrated to ensure end-to-end fault tolerance.

In the FPGA implementation, stabilizer measurements are mapped to multiply-accumulate circuits. Since quantum simulation is classical, the state is represented by probability distributions, but for small scales, wave function simulation can be used. HOLO chose the Monte Carlo method to average multiple run instances, thereby estimating error rates. This requires the FPGA to have efficient random sampling capability, implemented through linear feedback shift registers (LFSR) to generate pseudo-random sequences. The simulator also supports fault-tolerant simulation, including measurement errors and gate errors. By using multi-level concatenated codes to simulate nested surface codes, fault tolerance is further enhanced.

HOLO's FPGA-based surface code quantum simulator represents a breakthrough in the field of quantum computing. It not only demonstrates the potential of FPGA in quantum simulation but also provides a solid foundation for the realization of fault-tolerant quantum computers. As the technology matures, we can expect to witness an acceleration of the quantum revolution.

About MicroCloud Hologram Inc.

MicroCloud Hologram Inc. (NASDAQ: HOLO) is committed to the research and development and application of holographic technology. Its holographic technology services include holographic light detection and ranging (LiDAR) solutions based on holographic technology, holographic LiDAR point cloud algorithm architecture design, technical holographic imaging solutions, holographic LiDAR sensor chip design, and holographic vehicle intelligent vision technology, providing services to customers offering holographic advanced driving assistance systems (ADAS). MicroCloud Hologram Inc. provides holographic technology services to global customers. MicroCloud Hologram Inc. also provides holographic digital twin technology services and owns proprietary holographic digital twin technology resource libraries. Its holographic digital twin technology resource library utilizes a combination of holographic digital twin software, digital content, space data-driven data science, holographic digital cloud algorithms, and holographic 3D capture technology to capture shapes and objects in 3D holographic form. MicroCloud Hologram Inc. focuses on developments such as quantum computing and quantum holography, with cash reserves exceeding 3 billion RMB, and plans to invest more than 400 million in USD from the cash reserves to engage in blockchain development, quantum computing technology development, quantum holography technology development, and derivatives and technology development in frontier technology fields such as artificial intelligence AR. MicroCloud Hologram Inc.'s goal is to become a global leading quantum holography and quantum computing technology company.

Safe Harbor Statement

This press release contains forward-looking statements as defined by the Private Securities Litigation Reform Act of 1995. Forward-looking statements include statements concerning plans, objectives, goals, strategies, future events or performance, and underlying assumptions and other statements that are other than statements of historical facts. When the Company uses words such as "may," "will," "intend," "should," "believe," "expect," "anticipate," "project," "estimate," or similar expressions that do not relate solely to historical matters, it is making forward-looking statements. Forward-looking statements are not guarantees of future performance and involve risks and uncertainties that may cause the actual results to differ materially from the Company's expectations discussed in the forward-looking statements. These statements are subject to uncertainties and risks including, but not limited to, the following: the Company's goals and strategies; the Company's future business development; product and service demand and acceptance; changes in technology; economic conditions; reputation and brand; the impact of competition and pricing; government regulations; fluctuations in general economic; financial condition and results of operations; the expected growth of the holographic industry and business conditions in China and the international markets the Company plans to serve and assumptions underlying or related to any of the foregoing and other risks contained in reports filed by the Company with the Securities and Exchange Commission ("SEC"), including the Company's most recently filed Annual Report on Form 10-K and current report on Form 6-K and its subsequent filings. For these reasons, among others, investors are cautioned not to place undue reliance upon any forward-looking statements in this press release. Additional factors are discussed in the Company's filings with the SEC, which are available for review at www.sec.gov. The Company undertakes no obligation to publicly revise these forward-looking statements to reflect events or circumstances that arise after the date hereof.

 

 

 

View original content:https://www.prnewswire.com/news-releases/microcloud-hologram-inc-fpga-based-high-performance-surface-code-quantum-simulation-platform-efficient-error-correction-algorithm-validation-under-rotated-layout-302697199.html

SOURCE MicroCloud Hologram Inc.

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What performance improvement did HOLO report for its FPGA quantum simulator on distance-5 rotated codes?

HOLO reports a direct speed gain of more than 5-fold compared with GPU simulators. According to the company, this improvement applies to distance-5 rotated surface-code simulations and is coupled with about 30% lower power use.

How does HOLO's simulator reduce physical qubit requirements with rotated distance surface codes?

The rotated layout requires roughly half the qubits compared to standard surface codes for the same distance. According to the company, rotated distance d uses (d²+1)/2 data qubits and (d²-1)/2 ancilla qubits, saving near 50% resources.

What error-decoding algorithm does HOLO implement on FPGA for syndrome decoding (HOLO stock HOLO)?

HOLO implements a parallelized Minimum Weight Perfect Matching (MWPM) decoder on FPGA for syndrome decoding. According to the company, MWPM was optimized into parallel variants to reduce latency on the FPGA fabric.

What noise models and sampling methods does the HOLO FPGA simulator support for error-rate estimation?

The simulator supports depolarizing and bit-flip noise models and uses Monte Carlo averaging for error rates. According to the company, random sources include FPGA true-random elements and LFSR pseudo-random generators for sampling.

Will HOLO's FPGA simulator support fault-tolerant simulations for larger quantum algorithms like Shor or Grover?

HOLO says the simulator can integrate surface-code error correction into end-to-end algorithm simulations. According to the company, Shor and Grover simulations can include the surface-code loop and real-time syndrome feedback for fault-tolerance testing.

How will HOLO fund its quantum and frontier-technology development plans announced on Feb 25, 2026 (HOLO)?

HOLO plans to fund development from existing cash reserves, stating >3 billion RMB on hand and plans to invest more than $400 million. According to the company, these funds target blockchain, quantum computing, and related technologies.