At A Glance:

Quantum machine learning is an exciting and rapidly growing field at the intersection of quantum computing and machine learning. With the advent of the Noisy Intermediate-Scale Quantum (NISQ) era, we are witnessing a major shift in computing power and the potential for new breakthroughs in areas that were once considered intractable for classical computers.

In particular, quantum machine learning is expected to have a significant impact on two broad areas: non-convex optimization and combinatorial optimization. These are both problems that are notoriously difficult for classical computers to solve due to the exponential growth in computational complexity as the problem size increases.

By leveraging the powerful laws of quantum mechanics, such as superposition and entanglement, quantum machine learning has the potential to solve these problems significantly faster than classical algorithms. This is especially important as data sets continue to grow in size and complexity, making it increasingly difficult for classical computers to handle the computations involved.

While quantum machine learning is still a relatively new field, its potential impact on our future cannot be overstated. As we continue to explore the capabilities of NISQ-era quantum computers and beyond, we can expect to see even more exciting developments in this area and potentially solve some of the most complex problems facing our world today.

Here are some of the areas QML will disrupt:

Understanding nanoparticles

The creation of new materials through molecular and atomic maps

Molecular modeling to discover new drugs and medical research

Understanding the deeper makeup of the human body

Enhanced pattern recognition and classification

Furthering space exploration

Creating complete connected security through merging with IoT and blockchain

What We Do:

At Qulabs we are building Quantum tools, APIs, AI tools, APIs for various applications. Our solutions provide easy to use interface for leveraging Classical-Quantum algorithms. This Classical-Quantum hybrid approach is required in advance use cases to obtain speed up in optimization workloads in various applications involving Combinatorial Optimization Problems.

Quantum-Finance

is a very promising application of Quantum Computing. Among the huge variety of problems currently, Quantum Computing is good for portfolio optimization, stock-option pricing, and fraud detection. Many problems in finance can be expressed as optimization problems. These are tasks that are particularly hard for classical computers, but find a natural formulation using quantum optimization methods. In recent years, this field has experienced tremendous growth, partly due to the commercial availability of quantum annealers and quantum computers.

Our Solutions Are Quantum Agnostic:

As different problems are tailored for different platforms, we are building our algorithms to run on all possible quantum hardware platforms:

Superconducting

Photonic

Ion Traps

Our Solutions Are Quantum Inspired:

Suitable for the current NISQ era, we are developing new algorithms that can be applied now using different strategies:

Tensor Networks

Digital Annealing

Quantum Inspired Optimization

Artificial Intelligence

At A Glance:

Storing the quantum data is the key need of every quantum technology like quantum communication, quantum internet in multiple modules as quantum repeaters, routers.

Why Is It So Difficult:

Decoherence process, interference of environment of quantum data make it so delicate and difficult to store for a long time.

What We Do:

We are working on the solution of quantum storage by quantum optics and spectroscopy using theoretical and Mathematical modelling with the experimental realization of QM. We have developed a complete simulation package of Electromagnetically Induced Transparency (EIT) based QM, Atomic frequency comb (AFC) based QM. Using that we can simulate the experimental condition of QM. We are working on all the other QM protocols like Autler-Town Shifting (ATS) protocol, Control reversible inhomogeneous broadening (CRIB), Gradient echo memory (GEM). For overcoming the decoherence and noise effect we are using Dynamical Decoupling and ZEFOZ Techniques. Our plan is to make a complete quantum memory simulator that can simulate all kind of experimental protocols of QM and predict the experimental results before-hand. We are also working on the experimental realization of EIT and AFC-based QM in our Quantum optics lab.

Quantum Memory:

Decoherence and degradations of quantum data facilitate only limited distance transmission. Quantum repeaters are the key ingredients of the quantum internet for the distribution of long-distance entanglement between two distant quantum nodes. To synchronize the quantum data, in the BSM process, we need to store those multiple times in the form of quantum memory. Quantum memories are the key need of every quantum technology. We are developing the theoretical and experimental ground to test such quantum memories and their modifications based on the present need for quantum technology.

Figure Ref: nature.com/articles/nphoton.2009.231

Essentially these are of two types.

Electromagnetically Induced Transparency (EIT) And Autler-Towns Splitting (ATS) Based Quantum Memory:

EIT is the non-linear optical phenomenon that leads to an anomaly in the absorption profile of a 3-level atomic system like (Rb-vapour ensemble) in the presence of a strong control pulse (pump). This makes a narrow transparency window in the medium, which can be broadened by tuning the probe, (Autler-Towns Splitting). This makes the medium transparent for signal pulse (probe) near the resonance frequency and lowered the group velocity of it. The narrow We are working on quantum memory based on EIT-ATS protocols. We have developed the simulation of the mathematical model, that is being tested in our quantum optics lab.

Figure Ref: nature.com/articles/nphoton.2009.231

Atomic Frequency Comb (AFC), CRIB/GEM Based Quantum Memory:

Echo-based quantum memory gets traction because of its capability to store multimode photonic quantum data. By spectral hole burning and selective absorption techniques, an in homogeneously broadened transition can be tuned in a comb-like structure, this can store multimode photonic data, which can retrieve in the form of coherent echoes. We have developed a complete simulation of AFC, CRIB/GEM-based quantum memory, which can predict the experimental results of such QMs. We are in the way of experimental realization of these protocols with telecom wavelength storage with rare-earth ion-doped material- Er3+: Y2SiO4. For the suppressing noise at spin-wave storage level we are using “Dynamical Decoupling” and ZEFOZ techniques.

Figure Ref: nature.com/articles/nphoton.2009.231

Quantum Internet And Communication:

In the direction of super secure quantum communication quantum networking is our focus of research. Multiple areas in networking we are exploring based on the forefront of R&D

Figure Ref: https://en.x-mol.com/paper/article/5596772

Quantum Internet: A Solution Stack

Quantum Routing:

Quantum routing is the most necessary part of the network layer in the whole quantum networking stack. We have developed multiple routing algorithms for the quantum network, including sequential and parallel servicing of the demands in a ‘Hierarchical routing protocol’. We have also developed the “Shortcuts in quantum networks” using the pre-shared entanglement as the ‘virtual graph.’ We have predicted deadlock scenarios in parallel servicing of demands, and their avoidance techniques with replenishment protocols.

Quantum Network Simulator:

We have tested our “Shortcuts in the quantum network" in an existing open-source discrete-event simulator SeQueNCe by introducing some major changes in it. We observed the momentous decrement in the average latency that is the end–to–end entanglement time between the source and destination nodes in the quantum network.

At A Glance :

To design new protocols for Quantum Secure Direct Communication, finding flaws in existing protocols, and fixing the flaws by modifying the protocols.

What Is New :

Whereas the goal of Quantum Key Distribution (QKD) is to use quantum mechanical strategy to share a classical key for future classical cryptographic communication, Quantum Secure Direct Communication (QSDC), on the other hand, aims to send a classical message in the form of quantum states from one party to another using quantum channel, without requiring any secret key. When this communication happens in a duplex manner, i.e., between two parties back and forth, then it is called Quantum Dialogue (QD). Extending further, when this communication involves more than two parties, it is called Quantum Conference (QC). In recent times, several protocols for QSDC, QD, and QC have been developed and some weaknesses have also been discovered for some of them.

What We Do:

Novel QSDC Protocol: An alternative to QKD+Classical Ciphers.

Effcient Measurement Device Independent Quantum Dialogue Protocols:

Quantum dialogue is a process of securely exchanging messages between two parties, using quantum resources, without encryption.

Quantum Conference without Entanglement: Quantum conference is a process of securely exchanging messages between three or more parties, using quantum resources.

Quantum Multiparty XOR Computation: Every party computes the function without knowing the inputs from the other parties. Application in group key establishment.

Quantum Secure Direct Communication:

Whereas the goal of Quantum Key Distribution (QKD) is to use quantum mechanical strategy to share a classical key for future classical cryptographic communication, Quantum Secure Direct Communication (QSDC), on the other hand, aims to send a classical message in the form of quantum states from one party to another using quantum channel, without requiring any secret key. When this communication happens in a duplex manner, i.e., between two parties back and forth, then it is called Quantum Dialogue (QD). Extending further, when this communication involves more than two parties, it is called Quantum Conference (QC). In recent times, several protocols for QSDC, QD, and QC have been developed and some weaknesses have also been discovered for some of them. We at Qulabs work on designing new protocols, finding flaws in existing protocols, and fixing some of the flaws by modifying the protocols.

Quantum Attacks on Classical Ciphers:

Classical ciphers are of two types: public and private/symmetric. Most of the public key ciphers are attacked by Shor’s factoring algorithm or its variants. On the other hand, typically, quantum attacks on classical symmetric key ciphers are understood to be merely an application of Grover's search algorithm that effectively reduces the key size to half. However, recently cryptographers have developed cipher specific strategies to attack symmetric key schemes using quantum algorithms. This strategy is not generic and requires cipher-specific knowledge requires specific combinations of quantum operations. These attacks are parameterized and the efficiency of the attacks (in terms of time complexity and success probability) depends on customized cipher-specific tricks. We focus on quantum resource estimation of such attacks. This gives a quantitative measure of the required quantum resources, or in other words, quantum cost.

At A Glance :

We aim to develop secure blind computing protocols which can be implemented on the existing hardware available on the quantum cloud.

What Is New :

Blind Quantum Computing (BQC) refers to a set of protocols through which a client with ‘limited’ or ‘no’ quantum resources can perform quantum operation on a ‘blind’ quantum server; the server is blind in the sense that the server has no information about the task that it is performing. In our project, we aim to build and implement tools for a secure BQC, which makes it possible for users to test and perform their quantum operations and algorithms for both development as well as commercial applications.

A possible future hardware implementation of this simulator is important for the commercial as well as widespread usage of the quantum computation in our day-to-day life. We are interested in the recent developments in the field and want to create a bridge between the theoretical studies to the actual real-life applications. We want to use the presently available quantum architecture and use it in congruence with classical computing to provide implementations which can be applicable in real life applications.

Another goal that we aim to pursue is to identify the security aspects of the existing protocols.

What We Do:

In our search for a suitable blind computing simulator, we found that the key obstacle in this challenge is to put the circuit in an encrypted classical format for processing and the circuit model of computation does not always allow this.

Measurement-Based Quantum Computing (MBQC) model of computation, on the other hand, is much more conducive to specification in terms of classical entries and therefore has much more scope for conversion into an encrypted format. Although a large amount of theoretical research has been done in this direction, availability of a suitable simulator software for researchers is still on. To fill this gap, we are working on to build a MBQC simulator, which uses the circuit model in the backend and performs cluster state computations.

Simulating a cluster state, as is into its circuit equivalent, is a very complex task and requires a large amount of memory. We identified a few key elements which are causing the overhead and are trying to optimize these issues.

We are currently working on benchmarking the simulator and testing it for the known protocols

Although MBQC is equivalent to the circuit model of computation, there is very little work in literature which deals with algorithms or protocols based on MBQC. Users need to develop the intuition which helps them to convert circuit model into MBQC and vice-versa. It is also an intermediary step in the direction of using MBQC as a tool for Blind Quantum Computing. We are interested in building a complete Generic Blind Quantum Computing Machine, which can let users perform operations without sharing information of the operation and the result from the server.

MBQC is one possible approach towards reaching blindness, but similar circuit model protocols have also been built and have been tested experimentally in the past. However, these have not been converted into scalable products or tools which are accessible to the quantum community at large.

Fig: Quantum Delegated Computation-

Fig: Alice And Bob Performing Blind Quantum Computing-

A robust simulation tool to benchmark your quantum network architecture against different workloads. Simulate real-world quantum communication applications using our intuitive web interface. Designed for corporates to evaluate the power of quantum secure communications, and for academics to advance breakthroughs in quantum networking.

Introducing the world's first software quantum random number generator - a tool that uses quantum mechanics to produce high-quality random bits. This technology offers greater security and randomness compared to traditional methods that rely on predictable algorithms or physical processes. The software is accessible and affordable for all sizes of businesses and organizations and can be used remotely. It is ideal for applications in cyber security, data encryption, and more. Try the software quantum random number generator for a reliable and secure solution to your random number generation needs.

The rapid advancement of quantum computing technology has opened new possibilities in the field of portfolio optimization. We are creating RoboQop, an innovative software-based application that combines quantum computing capabilities with traditional roboadvisor functionality to offer enhanced portfolio management solutions. RoboQop utilizes the principles of Modern Portfolio Theory and incorporates various constraints, objective functions, and advanced analysis tools to optimize investment portfolios. Additionally, it leverages classical, heuristic, quantum, hybrid, and quantum-inspired algorithms to provide comprehensive and efficient portfolio optimization. The frontend and backend of RoboQop are developed using Angular and Django, respectively, ensuring a robust and user-friendly experience.

Quantum Computing takes advantage of Quantum phenomena Superposition principle, entanglement interference etc. to perform computation. Quantum Computing provides exponential speed up in solving problems like discrete logarithm, factorization etc. that were difficult for classical computers. The current state of quantum computers is not advanced enough. However, once large quantum computers are available, the mathematical problems that form the foundation of current asymmetric cryptography are easily solvable and make them easy to break, while the impact on symmetric cryptography will be relatively minor. “Harvest now decrypts later” is the strategy by which adversaries are trying to steal the data from the organization. Here, the adversaries store the encrypted data now and decrypt it later when the advanced quantum computer is available. This strategy indicates that current and future data is no longer secure against such attacks. Organizations need to be highly concerned about the security of their encrypted data and other confidential information. To protect past, present, and future data from adversaries, organizations must transition to quantum-safe cryptography. Our ChecQ tool offers specialized capabilities in detecting and addressing cryptographic quantum vulnerabilities in websites and software packages and map associated risk. By utilizing ChecQ, institutions can proactively safeguard their cryptographic systems and protect critical infrastructure from potential quantum computer cyberattacks.

ChecQ supports the analysis of websites, sources codes and binary files. The users can be assured about no data leakage as no user details or implementation details are uploaded or copied to server for analysis and assure secure implementational analysis. ChecQ provides users with an interactive interface and well-designed detailed result analysis windows.

The key features of ChecQ, Quantum Vulnerability Analysis Tool are:

Secure Quantum Vulnerability Scanning as no user details or implementation details are uploaded or copied to server.

Fast, efficient, and accurate static and dynamic vulnerability analysis.

Detailed assessment of cryptographic primitives.

Security based Pre-Quantum and Post-Quantum Vulnerability analyses and scoring.

Analysis report with Quantum vulnerability status, potential cryptographic risk assessment and risk mapping with grading and severity level.

User friendly interface enabling detailed line-by-line analysis of implementation.

Helps in analysis of security postures of the cryptographic algorithm implementations.

Post quantum remediation strategies to mitigate cryptographic risk.

The Blind Quantum Computing project at Qulabs aspires to achieve and provide secure delegated cloud quantum computing for any classical client through blind quantum computing technology. Qloudb is one of the tools we built to provide the facility to delegate universal quantum computation privately to servers (server itself doesn’t have the knowledge of intended computation) such as IBMQ, AWS-Braket and Azure Quantum platforms. Qloudb will serve as an intermediary layer to mask the actual quantum circuit of the user at the same time returning the same outcome in an irreversible manner. With applications provided by Qloudb a user can perform quantum machine learning over encryption quantum data, can perform quantum computations over encrypted graphs over many graph problems like graph clustering, maximum weighted-independent set problem etc., can perform protocol encryption and much more.