Cibiyar Kwakwalwar Kwayoyin Halitta don Lissafin Kwayoyin Halitta Mai Laushi

Teburin Abubuwan Ciki

1. Gabatarwa

Cibiyoyin kwakwalwa sun sami nasarori masu ban mamaki a masana'antu da ilimi, amma suna fuskantar ƙalubale masu yawa a cikin sikelin da kuma kwaikwayon tsarin kwayoyin halitta. Cibiyoyin kwakwalwa na al'ada suna fama da sararin samaniya mai girma na kwayoyin halitta da kuma ƙaruwar farashin horo yayin da girman cibiyar sadarwa ke girma. Lissafin kwayoyin halitta yana ba da madadin mai ban sha'awa, amma aiwatar da yanzu na fuskantar manyan ƙalubalen aiwatarwa na zahiri.

Wannan takarda ta gabatar da wani sabon samfuri na cibiyar kwakwalwar kwayoyin halitta don lissafin kwayoyin halitta mai laushi wanda ke amfani da ayyukan qubit guda da aka sarrafa na al'ada da ma'auni akan tsarin kwayoyin halitta na duniya. Hanyarmu tana rage matsalolin aiwatarwa sosai ta hanyar amfani da rugujewar muhalli da ke faruwa a zahiri maimakon ɗaukar ta azaman lahani.

2. Hanyar Aiki

2.1 Neurons na Kwayoyin Halitta Masu Laushi

Neurons na kwayoyin halitta masu laushi sun zama tushen ginin samfurin mu na cibiyar kwakwalwar kwayoyin halitta. Kowace neuron tana aiki ta amfani da ayyukan qubit guda kawai, ayyukan qubit guda da aka sarrafa na al'ada, da ma'auni. Wannan zaɓin ƙira yana rage rikitarwar aiwatarwa ta zahiri sosai idan aka kwatanta da hanyoyin lissafin kwayoyin halitta na al'ada waɗanda ke buƙatar haɗin qubit da yawa da rikitattun ƙofofin kwayoyin halitta.

2.2 Tsarin Cibiyar Sadarwa

Tsarin cibiyar sadarwa ya ƙunshi yadudduka da yawa na neurons na kwayoyin halitta masu laushi waɗanda aka haɗa ta hanyoyin sarrafawa na al'ada. Ana saka bayanan shiga cikin jihohin kwayoyin halitta, ana sarrafa su ta hanyar ayyukan kwayoyin halitta na bi da bi, kuma ana auna su don samar da fitarwa na al'ada. Wannan hanyar haɗin kwayoyin halitta da na al'ada yana ba da damar ingantaccen ingantacciyar hanyar amfani da algorithms na ingantawa na al'ada yayin kiyaye fa'idodin kwayoyin halitta.

3. Aiwatar da Fasaha

3.1 Tsarin Lissafi

Cibiyar kwakwalwar kwayoyin halitta tana aiki akan ka'idar juyin halittar jihar kwayoyin halitta ta hanyar jujjuyawar qubit guda da ma'auni. Babban aikin ana iya wakilta shi kamar haka:

$\psi_{out} = M(U(\theta)\psi_{in})$

inda $U(\theta)$ ke wakiltar jujjuyawar qubit guda da aka daidaita sigogi kuma $M$ yana nuna aikin ma'auni. Ingantaccen cibiyar sadarwa yana rage aikin farashi:

$C(\theta) = \sum_{i=1}^{N} L(f(\psi_i; \theta), y_i)$

inda $L$ shine aikin asara, $f(\psi_i; \theta)$ shine fitarwar cibiyar sadarwa, kuma $y_i$ shine ƙimar manufa.

3.2 Binciken Rikicin Kwayoyin Halitta

Bincikenmu ya nuna cewa alaƙar kwayoyin halitta da ke da alaƙar rikicin kwayoyin halitta mara sifili suna nan a cikin neurons na kwayoyin halitta. Rikicin kwayoyin halitta $D(\rho_{AB})$ tsakanin ƙananan tsarin A da B an ayyana shi kamar haka:

$D(\rho_{AB}) = I(\rho_{AB}) - J(\rho_{AB})$

inda $I(\rho_{AB})$ shine bayanan haɗin gwiwar kwayoyin halitta kuma $J(\rho_{AB})$ shine alaƙar al'ada. Kasancewar rikicin kwayoyin halitta yana nuna haƙiƙanin alaƙar kwayoyin halitta bayan alaƙar al'ada, yana ba da gudummawa ga ikon lissafi na cibiyar sadarwa.

4. Sakamakon Gwaji

4.1 Gane Lambobin Hannu

Mun gwada samfurinmu akan bayanan gane lambobin hannu na MNIST. Cibiyar kwakwalwar kwayoyin halitta ta sami daidaiton rarrabuwa kwatankwacin cibiyoyin kwakwalwa na al'ada yayin amfani da ƙananan albarkatun lissafi. Cibiyar sadarwa ta nuna ƙarfi na musamman wajen gane ƙirar lambobi da karkatattu da masu hayaniya, yana nuna ƙarfinta ga bambance-bambancen shigarwa.

4.2 Ayyukan Rarrabuwa Mara Layi

An gwada samfurin akan ayyukan rarrabuwa mara layi daban-daban ciki har da matsalolin XOR da rarrabuwar bayanan karkace. Sakamakon ya nuna cewa cibiyar mu ta kwakwalwar kwayoyin halitta tana da ikon rarrabuwa mara layi mai ban mamaki, ta raba iyakokin yanke shawara masu rikitarwa waɗanda ke ƙalubalantar masu rarraba layi na al'ada. Cibiyar sadarwa ta ci gaba da yin aiki mai girma ko ƙarƙashin yanayi masu yawan hayaniya, yana nuna ƙarfi mai amfani don aikace-aikacen duniya.

5. Aiwatar da Lambar

A ƙasa akwai sauƙaƙan lambar ƙirar da aka aiwatar na cibiyar kwakwalwar kwayoyin halitta mai laushi:

class SoftQuantumNeuron:
    def __init__(self, input_size):
        self.weights = initialize_quantum_parameters(input_size)
        self.measurement_basis = choose_measurement_basis()
    
    def forward(self, input_state):
        # Saka shigarwar al'ada zuwa jihar kwayoyin halitta
        quantum_state = encode_input(input_state)
        
        # Aiwatar da jujjuyawar qubit guda da aka daidaita sigogi
        for i in range(len(self.weights)):
            quantum_state = apply_rotation(quantum_state, self.weights[i])
        
        # Auna a cikin zaɓaɓɓen tushe
        output = measure_quantum_state(quantum_state, self.measurement_basis)
        return output

class QuantumNeuralNetwork:
    def __init__(self, architecture):
        self.layers = [SoftQuantumNeuron(size) for size in architecture]
    
    def train(self, dataset, epochs):
        for epoch in range(epochs):
            for data, target in dataset:
                # Wucewa gaba
                output = self.forward(data)
                
                # Lissafa asarar al'ada
                loss = compute_loss(output, target)
                
                # Sabunta sigogi ta amfani da mai ingantawa na al'ada
                self.update_parameters(loss)

6. Aikace-aikace na Gaba

Tsarin lissafin kwayoyin halitta mai laushi yana buɗe hanyoyin aikace-aikace da yawa a cikin na'urorin kwayoyin halitta na kusa. Yuwuwar aikace-aikace sun haɗa da:

• Kwayoyin Halitta na Injin Koyo: Ingantaccen gane tsari da ayyukan rarrabuwa akan bayanan kwayoyin halitta
• Kimiyyar Kayan Aiki: Kwaikwayon tsarin kwayoyin halitta na jiki da yawa don gano magunguna da ƙirar kayan aiki
• Matsalolin Ingantawa: Magance rikitattun matsalolin ingantawa a cikin kayan aiki da kuɗi
• Lissafi Mai Jure wa Hayaniya: Aikace-aikace a cikin wuraren da rugujewar kwayoyin halitta ke da muhimmanci
• Lissafin Kwayoyin Halitta na Gefe: Tura aiki akan ƙananan na'urorin kwayoyin halitta don ayyuka na musamman

Hanyoyin bincike na gaba sun haɗa da sikelin gine-gine zuwa manyan tsarin kwayoyin halitta, haɓaka aiwatar da kayan aiki na musamman, da bincika aikace-aikace a cikin gyaran kurakurai na kwayoyin halitta da lissafin rashin kuskure.

Bincike na Asali

7. Bayanan Kafa

1. Zhu, J. Y., Park, T., Isola, P., & Efros, A. A. (2017). Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks. IEEE International Conference on Computer Vision.
2. Preskill, J. (2018). Quantum Computing in the NISQ era and beyond. Quantum, 2, 79.
3. Biamonte, J., Wittek, P., Pancotti, N., Rebentrost, P., Wiebe, N., & Lloyd, S. (2017). Quantum machine learning. Nature, 549(7671), 195-202.
4. Farhi, E., Goldstone, J., & Gutmann, S. (2014). A Quantum Approximate Optimization Algorithm. arXiv:1411.4028.
5. IBM Qiskit Team. (2020). Qiskit Textbook: Quantum Machine Learning.
6. Google Quantum AI Team. (2021). Quantum Neural Network Research Overview.
7. Nielsen, M. A., & Chuang, I. L. (2010). Quantum Computation and Quantum Information. Cambridge University Press.